{"about":{"non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","site":"https://codewithpapers.app","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page","syntology":{"site":"https://syntology.ai","developers":"https://syntology.ai/developers","mcp":{"server":"https://syntology.ai/mcp","transport":"streamable-http","server_card":"https://syntology.ai/.well-known/mcp/server-card.json","auth":{"type":"trial token, no account","trial_token":"https://syntology.ai/api/oauth/trial/token","method":"POST","docs":"https://syntology.ai/developers"}},"have":"https://syntology.ai/api/graph/have?x=<method, arXiv id or title> (free, answers coverage only)","paper_base":"https://syntology.ai/paper/","atlas_base":"https://app.syntology.ai/?focus="},"machine_readable":[{"url":"https://codewithpapers.app/llms.txt","what":"the machine catalog: every machine-readable file, counted"},{"url":"https://codewithpapers.app/index/manifest.json","what":"paper-to-code index by arXiv id, with Syntology's counts"},{"url":"https://codewithpapers.app/search/manifest.json","what":"site search index (titles, authors) and its files"},{"url":"https://codewithpapers.app/download","what":"bulk files: Syntology's layer, described there"},{"url":"https://codewithpapers.app/build_manifest.json","what":"the build record: inputs, counts, exclusions, probes"}]},"url":"/method/bottleneck-residual-block/papers/ran/2","list_of":"/method/bottleneck-residual-block","method":"Bottleneck Residual Block","archive":{"snapshot":"2025-07-28"},"syntology_read_at":"2026-09-28T10:30:06+00:00","order":"ran","order_definition":"only papers where Syntology ran at least one harvested sample; date (newest first), ties by arXiv id","caption":"We ran code from the paper's repository; we did not isolate this method inside it.","absence":"A paper missing from this list is not a recorded non-run: it may have no arXiv id, no harvested code, or only samples that have not run yet.","page":2,"pages_in_order":4,"rows_per_page":100,"rows":[101,200],"of":315,"counts":{"archive_papers_tagged":2049,"with_a_code_link":1020,"where_syntology_ran_a_sample":315,"not_listed_spam_title":0,"listed":2049,"listed_where_code_ran":315,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":263,"every_run_a_failure_of_syntologys_instrument":52,"listed_with_a_run_with_no_instrument_failure":263,"listed_every_run_a_failure_of_syntologys_instrument":52,"filter":{"states":["a run with no instrument failure","any run, instrument failures included"],"default":"a run with no instrument failure","note":"on the 'only where code ran' pages the default hides, in the browser, the rows where every run was a failure of Syntology's instrument; the second state shows them again. Rows are hidden, never re-ordered; these twins list every row"}},"definition":"distinct papers the archive tags; 'where Syntology ran a sample' counts papers with at least one harvested sample that ran, which is not a correctness claim"},"first_page":"/method/bottleneck-residual-block/papers/ran/1","prev":"/method/bottleneck-residual-block/papers/ran/1","next":"/method/bottleneck-residual-block/papers/ran/3","papers":[{"paper":"/paper/lambdanetworks-modeling-long-range-1","slug":"lambdanetworks-modeling-long-range-1","title":"LambdaNetworks: Modeling Long-Range Interactions Without Attention","date":"2021-02-17","arxiv_id":"2102.08602","n_code_links":7,"syntology":{"ran":2,"of":2,"n_ran_checked":0,"n_instrument":2,"unverified":0,"pointer_only":2,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 2 where Syntology's instrument failed) · 0 unverified","official":null}},{"paper":"/paper/brecq-pushing-the-limit-of-post-training-1","slug":"brecq-pushing-the-limit-of-post-training-1","title":"BRECQ: Pushing the Limit of Post-Training Quantization by Block Reconstruction","date":"2021-02-10","arxiv_id":"2102.05426","n_code_links":3,"syntology":{"ran":5,"of":5,"n_ran_checked":2,"n_instrument":3,"unverified":0,"pointer_only":3,"phrase":"5 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 2 honoured, 0 violated, 0 with no contract checked; 3 where Syntology's instrument failed) · 0 unverified","official":{"repos":["yhhhli/BRECQ"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":0,"ran_from_kinds":["official","unlocated"]}}},{"paper":"/paper/mali-a-memory-efficient-and-reverse-accurate-1","slug":"mali-a-memory-efficient-and-reverse-accurate-1","title":"MALI: A memory efficient and reverse accurate integrator for Neural ODEs","date":"2021-02-09","arxiv_id":"2102.04668","n_code_links":1,"syntology":{"ran":2,"of":4,"n_ran_checked":2,"n_instrument":0,"unverified":2,"pointer_only":0,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 2 honoured, 0 violated, 0 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified","official":{"repos":["juntang-zhuang/TorchDiffEqPack"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":2,"ran_from_kinds":["official"]}}},{"paper":"/paper/spike-based-residual-blocks","slug":"spike-based-residual-blocks","title":"Deep Residual Learning in Spiking Neural Networks","date":"2021-02-08","arxiv_id":"2102.04159","n_code_links":1,"syntology":{"ran":2,"of":3,"n_ran_checked":0,"n_instrument":2,"unverified":1,"pointer_only":3,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 2 where Syntology's instrument failed) · 1 unverified","official":{"repos":["fangwei123456/Spike-Element-Wise-ResNet"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["community"]}}},{"paper":"/paper/gnn-rl-compression-topology-aware-network","slug":"gnn-rl-compression-topology-aware-network","title":"Topology-Aware Network Pruning using Multi-stage Graph Embedding and Reinforcement Learning","date":"2021-02-05","arxiv_id":"2102.03214","n_code_links":1,"syntology":{"ran":3,"of":4,"n_ran_checked":1,"n_instrument":2,"unverified":1,"pointer_only":4,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 1 honoured, 0 violated, 0 with no contract checked; 2 where Syntology's instrument failed) · 1 unverified","official":{"repos":["yusx-swapp/gnn-rl-model-compression"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":"/paper/ml-doctor-holistic-risk-assessment-of","slug":"ml-doctor-holistic-risk-assessment-of","title":"ML-Doctor: Holistic Risk Assessment of Inference Attacks Against Machine Learning Models","date":"2021-02-04","arxiv_id":"2102.02551","n_code_links":1,"syntology":{"ran":1,"of":3,"n_ran_checked":0,"n_instrument":1,"unverified":2,"pointer_only":0,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 2 unverified","official":{"repos":["liuyugeng/ml-doctor"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":2,"ran_from_kinds":["official"]}}},{"paper":"/paper/daf-re-a-challenging-crowd-sourced-large","slug":"daf-re-a-challenging-crowd-sourced-large","title":"DAF:re: A Challenging, Crowd-Sourced, Large-Scale, Long-Tailed Dataset For Anime Character Recognition","date":"2021-01-21","arxiv_id":"2101.08674","n_code_links":2,"syntology":{"ran":1,"of":1,"n_ran_checked":0,"n_instrument":1,"unverified":0,"pointer_only":1,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","official":{"repos":["arkel23/animesion"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"paper":"/paper/online-bag-of-visual-words-generation-for","slug":"online-bag-of-visual-words-generation-for","title":"OBoW: Online Bag-of-Visual-Words Generation for Self-Supervised Learning","date":"2020-12-21","arxiv_id":"2012.11552","n_code_links":3,"syntology":{"ran":3,"of":3,"n_ran_checked":0,"n_instrument":3,"unverified":0,"pointer_only":3,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 3 where Syntology's instrument failed) · 0 unverified","official":{"repos":["valeoai/obow"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":"/paper/simple-copy-paste-is-a-strong-data","slug":"simple-copy-paste-is-a-strong-data","title":"Simple Copy-Paste is a Strong Data Augmentation Method for Instance Segmentation","date":"2020-12-13","arxiv_id":"2012.07177","n_code_links":5,"syntology":{"ran":2,"of":2,"n_ran_checked":1,"n_instrument":1,"unverified":0,"pointer_only":0,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 1 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","official":{"repos":["tensorflow/tpu"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"paper":"/paper/padim-a-patch-distribution-modeling-framework","slug":"padim-a-patch-distribution-modeling-framework","title":"PaDiM: a Patch Distribution Modeling Framework for Anomaly Detection and Localization","date":"2020-11-17","arxiv_id":"2011.08785","n_code_links":26,"syntology":{"ran":7,"of":7,"n_ran_checked":2,"n_instrument":5,"unverified":0,"pointer_only":3,"phrase":"7 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 1 honoured, 1 violated, 0 with no contract checked; 5 where Syntology's instrument failed) · 0 unverified","official":null}},{"paper":"/paper/speech-simclr-combining-contrastive-and","slug":"speech-simclr-combining-contrastive-and","title":"Speech SIMCLR: Combining Contrastive and Reconstruction Objective for Self-supervised Speech Representation Learning","date":"2020-10-27","arxiv_id":"2010.13991","n_code_links":1,"syntology":{"ran":4,"of":5,"n_ran_checked":4,"n_instrument":0,"unverified":1,"pointer_only":0,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 0 violated, 4 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","official":{"repos":["athena-team/athena"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":"/paper/viewmaker-networks-learning-views-for-1","slug":"viewmaker-networks-learning-views-for-1","title":"Viewmaker Networks: Learning Views for Unsupervised Representation Learning","date":"2020-10-14","arxiv_id":"2010.07432","n_code_links":1,"syntology":{"ran":2,"of":4,"n_ran_checked":2,"n_instrument":0,"unverified":2,"pointer_only":0,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified","official":{"repos":["alextamkin/viewmaker"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":2,"ran_from_kinds":["official"]}}},{"paper":"/paper/meta-aggregating-networks-for-class-1","slug":"meta-aggregating-networks-for-class-1","title":"Adaptive Aggregation Networks for Class-Incremental Learning","date":"2020-10-10","arxiv_id":"2010.05063","n_code_links":2,"syntology":{"ran":4,"of":4,"n_ran_checked":1,"n_instrument":3,"unverified":0,"pointer_only":2,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 3 where Syntology's instrument failed) · 0 unverified","official":{"repos":["yaoyao-liu/class-incremental-learning"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":"/paper/where-are-the-facts-searching-for-fact","slug":"where-are-the-facts-searching-for-fact","title":"Where Are the Facts? Searching for Fact-checked Information to Alleviate the Spread of Fake News","date":"2020-10-07","arxiv_id":"2010.03159","n_code_links":2,"syntology":{"ran":5,"of":5,"n_ran_checked":5,"n_instrument":0,"unverified":0,"pointer_only":0,"phrase":"5 ran (of which 0 constructed an object rather than computing a result; 5 with no instrument failure: 0 honoured, 0 violated, 5 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","official":{"repos":["nguyenvo09/EMNLP2020"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":"/paper/understanding-self-supervised-learning-with","slug":"understanding-self-supervised-learning-with","title":"Understanding Self-supervised Learning with Dual Deep Networks","date":"2020-10-01","arxiv_id":"2010.00578","n_code_links":2,"syntology":{"ran":1,"of":1,"n_ran_checked":0,"n_instrument":1,"unverified":0,"pointer_only":1,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","official":{"repos":["facebookresearch/luckmatters"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":"/paper/group-whitening-balancing-learning-efficiency","slug":"group-whitening-balancing-learning-efficiency","title":"Group Whitening: Balancing Learning Efficiency and Representational Capacity","date":"2020-09-28","arxiv_id":"2009.13333","n_code_links":1,"syntology":{"ran":5,"of":5,"n_ran_checked":2,"n_instrument":3,"unverified":0,"pointer_only":1,"phrase":"5 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 3 where Syntology's instrument failed) · 0 unverified","official":null}},{"paper":"/paper/anomalous-diffusion-dynamics-of-learning-in","slug":"anomalous-diffusion-dynamics-of-learning-in","title":"Anomalous diffusion dynamics of learning in deep neural networks","date":"2020-09-22","arxiv_id":"2009.10588","n_code_links":1,"syntology":{"ran":9,"of":11,"n_ran_checked":9,"n_instrument":0,"unverified":2,"pointer_only":4,"phrase":"9 ran (of which 0 constructed an object rather than computing a result; 9 with no instrument failure: 0 honoured, 0 violated, 9 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified","official":{"repos":["ifgovh/Anomalous-diffusion-dynamics-of-SGD"],"state":"official (archive's flag): 9 ran","n_ran":9,"n_constructed":0,"n_ran_no_instrument_failure":9,"n_unverified":2,"ran_from_kinds":["official"]}}},{"paper":"/paper/contrastive-clustering","slug":"contrastive-clustering","title":"Contrastive Clustering","date":"2020-09-21","arxiv_id":"2009.09687","n_code_links":2,"syntology":{"ran":7,"of":7,"n_ran_checked":7,"n_instrument":0,"unverified":0,"pointer_only":3,"phrase":"7 ran (of which 2 constructed an object rather than computing a result; 7 with no instrument failure: 0 honoured, 0 violated, 7 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","official":{"repos":["Yunfan-Li/Contrastive-Clustering"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":0,"ran_from_kinds":["found_in_text","listed","official"]}}},{"paper":"/paper/wavegrad-estimating-gradients-for-waveform","slug":"wavegrad-estimating-gradients-for-waveform","title":"WaveGrad: Estimating Gradients for Waveform Generation","date":"2020-09-02","arxiv_id":"2009.00713","n_code_links":7,"syntology":{"ran":3,"of":3,"n_ran_checked":2,"n_instrument":1,"unverified":0,"pointer_only":1,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","official":null}},{"paper":"/paper/a-framework-for-contrastive-self-supervised","slug":"a-framework-for-contrastive-self-supervised","title":"A Framework For Contrastive Self-Supervised Learning And Designing A New Approach","date":"2020-08-31","arxiv_id":"2009.00104","n_code_links":2,"syntology":{"ran":1,"of":2,"n_ran_checked":1,"n_instrument":0,"unverified":1,"pointer_only":0,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","official":null}},{"paper":"/paper/unsupervised-feature-learning-by-cross-level","slug":"unsupervised-feature-learning-by-cross-level","title":"Unsupervised Feature Learning by Cross-Level Instance-Group Discrimination","date":"2020-08-09","arxiv_id":"2008.03813","n_code_links":2,"syntology":{"ran":6,"of":8,"n_ran_checked":4,"n_instrument":2,"unverified":2,"pointer_only":1,"phrase":"6 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 0 violated, 4 with no contract checked; 2 where Syntology's instrument failed) · 2 unverified","official":{"repos":["frank-xwang/CLD-UnsupervisedLearning"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":2,"ran_from_kinds":["official"]}}},{"paper":"/paper/continuous-in-depth-neural-networks","slug":"continuous-in-depth-neural-networks","title":"Continuous-in-Depth Neural Networks","date":"2020-08-05","arxiv_id":"2008.02389","n_code_links":4,"syntology":{"ran":4,"of":6,"n_ran_checked":0,"n_instrument":4,"unverified":2,"pointer_only":6,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 4 where Syntology's instrument failed) · 2 unverified","official":{"repos":["afqueiruga/ContinuousNet"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"paper":"/paper/encoding-in-style-a-stylegan-encoder-for","slug":"encoding-in-style-a-stylegan-encoder-for","title":"Encoding in Style: a StyleGAN Encoder for Image-to-Image Translation","date":"2020-08-03","arxiv_id":"2008.00951","n_code_links":10,"syntology":{"ran":16,"of":16,"n_ran_checked":13,"n_instrument":3,"unverified":0,"pointer_only":1,"phrase":"16 ran (of which 0 constructed an object rather than computing a result; 13 with no instrument failure: 1 honoured, 0 violated, 12 with no contract checked; 3 where Syntology's instrument failed) · 0 unverified","official":{"repos":["eladrich/pixel2style2pixel"],"state":"official: no sample here; runs from other or unrecorded repositories","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed","unlocated"]}}},{"paper":"/paper/improving-robustness-against-common","slug":"improving-robustness-against-common","title":"Improving robustness against common corruptions by covariate shift adaptation","date":"2020-06-30","arxiv_id":"2006.16971","n_code_links":2,"syntology":{"ran":3,"of":3,"n_ran_checked":0,"n_instrument":3,"unverified":0,"pointer_only":0,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 3 where Syntology's instrument failed) · 0 unverified","official":{"repos":["bethgelab/robustness"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":"/paper/paying-more-attention-to-snapshots-of","slug":"paying-more-attention-to-snapshots-of","title":"Paying more attention to snapshots of Iterative Pruning: Improving Model Compression via Ensemble Distillation","date":"2020-06-20","arxiv_id":"2006.11487","n_code_links":1,"syntology":{"ran":4,"of":8,"n_ran_checked":3,"n_instrument":1,"unverified":4,"pointer_only":2,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 1 where Syntology's instrument failed) · 4 unverified","official":{"repos":["lehduong/kesi"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":4,"ran_from_kinds":["official"]}}},{"paper":"/paper/unsupervised-learning-of-visual-features-by","slug":"unsupervised-learning-of-visual-features-by","title":"Unsupervised Learning of Visual Features by Contrasting Cluster Assignments","date":"2020-06-17","arxiv_id":"2006.09882","n_code_links":18,"syntology":{"ran":13,"of":17,"n_ran_checked":6,"n_instrument":7,"unverified":4,"pointer_only":6,"phrase":"13 ran (of which 4 constructed an object rather than computing a result; 6 with no instrument failure: 1 honoured, 1 violated, 4 with no contract checked; 7 where Syntology's instrument failed) · 4 unverified","official":{"repos":["facebookresearch/swav"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"paper":"/paper/big-self-supervised-models-are-strong-semi","slug":"big-self-supervised-models-are-strong-semi","title":"Big Self-Supervised Models are Strong Semi-Supervised Learners","date":"2020-06-17","arxiv_id":"2006.10029","n_code_links":9,"syntology":{"ran":4,"of":6,"n_ran_checked":4,"n_instrument":0,"unverified":2,"pointer_only":0,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 0 violated, 4 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified","official":{"repos":["google-research/simclr"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"paper":"/paper/directional-pruning-of-deep-neural-networks","slug":"directional-pruning-of-deep-neural-networks","title":"Directional Pruning of Deep Neural Networks","date":"2020-06-16","arxiv_id":"2006.09358","n_code_links":1,"syntology":{"ran":1,"of":1,"n_ran_checked":1,"n_instrument":0,"unverified":0,"pointer_only":1,"phrase":"1 ran (of which 1 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified; the one sample that ran constructed an object rather than computing a result","official":{"repos":["donlan2710/gRDA-Optimizer"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":1,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":"/paper/bootstrap-your-own-latent-a-new-approach-to","slug":"bootstrap-your-own-latent-a-new-approach-to","title":"Bootstrap your own latent: A new approach to self-supervised Learning","date":"2020-06-13","arxiv_id":"2006.07733","n_code_links":31,"syntology":{"ran":62,"of":79,"n_ran_checked":42,"n_instrument":20,"unverified":17,"pointer_only":46,"phrase":"62 ran (of which 19 constructed an object rather than computing a result; 42 with no instrument failure: 4 honoured, 1 violated, 37 with no contract checked; 20 where Syntology's instrument failed) · 17 unverified","official":{"repos":["deepmind/deepmind-research"],"state":"official: no sample here; runs from other or unrecorded repositories","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed","unlocated"]}}},{"paper":"/paper/interpolation-between-residual-and-non","slug":"interpolation-between-residual-and-non","title":"Interpolation between Residual and Non-Residual Networks","date":"2020-06-10","arxiv_id":"2006.05749","n_code_links":1,"syntology":{"ran":2,"of":2,"n_ran_checked":2,"n_instrument":0,"unverified":0,"pointer_only":2,"phrase":"2 ran (of which 2 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified; every one of the 2 samples that ran constructed an object rather than computing a result","official":null}},{"paper":"/paper/visual-transformers-token-based-image","slug":"visual-transformers-token-based-image","title":"Visual Transformers: Token-based Image Representation and Processing for Computer Vision","date":"2020-06-05","arxiv_id":"2006.03677","n_code_links":8,"syntology":{"ran":6,"of":6,"n_ran_checked":6,"n_instrument":0,"unverified":0,"pointer_only":0,"phrase":"6 ran (of which 0 constructed an object rather than computing a result; 6 with no instrument failure: 0 honoured, 0 violated, 6 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","official":null}},{"paper":"/paper/adahessian-an-adaptive-second-order-optimizer","slug":"adahessian-an-adaptive-second-order-optimizer","title":"ADAHESSIAN: An Adaptive Second Order Optimizer for Machine Learning","date":"2020-06-01","arxiv_id":"2006.00719","n_code_links":4,"syntology":{"ran":5,"of":11,"n_ran_checked":4,"n_instrument":1,"unverified":6,"pointer_only":1,"phrase":"5 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 0 violated, 4 with no contract checked; 1 where Syntology's instrument failed) · 6 unverified","official":{"repos":["amirgholami/adahessian"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":5,"ran_from_kinds":["listed","official"]}}},{"paper":"/paper/clocs-contrastive-learning-of-cardiac-signals","slug":"clocs-contrastive-learning-of-cardiac-signals","title":"CLOCS: Contrastive Learning of Cardiac Signals Across Space, Time, and Patients","date":"2020-05-27","arxiv_id":"2005.13249","n_code_links":2,"syntology":{"ran":2,"of":2,"n_ran_checked":1,"n_instrument":1,"unverified":0,"pointer_only":2,"phrase":"2 ran (of which 1 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","official":{"repos":["danikiyasseh/CLOCS"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed","official"]}}},{"paper":"/paper/enabling-deep-spiking-neural-networks-with-1","slug":"enabling-deep-spiking-neural-networks-with-1","title":"Enabling Deep Spiking Neural Networks with Hybrid Conversion and Spike Timing Dependent Backpropagation","date":"2020-05-04","arxiv_id":"2005.01807","n_code_links":1,"syntology":{"ran":1,"of":4,"n_ran_checked":1,"n_instrument":0,"unverified":3,"pointer_only":4,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 3 unverified","official":{"repos":["nitin-rathi/hybrid-snn-conversion"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":3,"ran_from_kinds":["official"]}}},{"paper":"/paper/explaining-how-deep-neural-networks-forget-by","slug":"explaining-how-deep-neural-networks-forget-by","title":"Explaining How Deep Neural Networks Forget by Deep Visualization","date":"2020-05-03","arxiv_id":"2005.01004","n_code_links":2,"syntology":{"ran":1,"of":1,"n_ran_checked":1,"n_instrument":0,"unverified":0,"pointer_only":0,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 1 honoured, 0 violated, 0 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","official":{"repos":["giangnguyen2412/dissect_catastrophic_forgetting"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":"/paper/ultra-fast-structure-aware-deep-lane","slug":"ultra-fast-structure-aware-deep-lane","title":"Ultra Fast Structure-aware Deep Lane Detection","date":"2020-04-24","arxiv_id":"2004.11757","n_code_links":10,"syntology":{"ran":2,"of":3,"n_ran_checked":1,"n_instrument":1,"unverified":1,"pointer_only":3,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 1 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 1 unverified","official":{"repos":["cfzd/Ultra-Fast-Lane-Detection"],"state":"official: no sample here; runs from other or unrecorded repositories","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed","unlocated"]}}},{"paper":"/paper/supervised-contrastive-learning","slug":"supervised-contrastive-learning","title":"Supervised Contrastive Learning","date":"2020-04-23","arxiv_id":"2004.11362","n_code_links":26,"syntology":{"ran":17,"of":23,"n_ran_checked":14,"n_instrument":3,"unverified":6,"pointer_only":5,"phrase":"17 ran (of which 0 constructed an object rather than computing a result; 14 with no instrument failure: 2 honoured, 0 violated, 12 with no contract checked; 3 where Syntology's instrument failed) · 6 unverified","official":{"repos":["HobbitLong/SupContrast","google-research/google-research"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"paper":"/paper/dynamic-r-cnn-towards-high-quality-object","slug":"dynamic-r-cnn-towards-high-quality-object","title":"Dynamic R-CNN: Towards High Quality Object Detection via Dynamic Training","date":"2020-04-13","arxiv_id":"2004.06002","n_code_links":3,"syntology":{"ran":9,"of":18,"n_ran_checked":9,"n_instrument":0,"unverified":9,"pointer_only":1,"phrase":"9 ran (of which 0 constructed an object rather than computing a result; 9 with no instrument failure: 0 honoured, 1 violated, 8 with no contract checked; 0 where Syntology's instrument failed) · 9 unverified","official":{"repos":["hkzhang95/DynamicRCNN"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":1,"ran_from_kinds":["listed","official"]}}},{"paper":"/paper/fda-fourier-domain-adaptation-for-semantic","slug":"fda-fourier-domain-adaptation-for-semantic","title":"FDA: Fourier Domain Adaptation for Semantic Segmentation","date":"2020-04-11","arxiv_id":"2004.05498","n_code_links":3,"syntology":{"ran":2,"of":3,"n_ran_checked":1,"n_instrument":1,"unverified":1,"pointer_only":3,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 1 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 1 unverified","official":{"repos":["YanchaoYang/FDA"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":1,"ran_from_kinds":["official","unlocated"]}}},{"paper":"/paper/improved-residual-networks-for-image-and","slug":"improved-residual-networks-for-image-and","title":"Improved Residual Networks for Image and Video Recognition","date":"2020-04-10","arxiv_id":"2004.04989","n_code_links":2,"syntology":{"ran":3,"of":4,"n_ran_checked":1,"n_instrument":2,"unverified":1,"pointer_only":1,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 2 where Syntology's instrument failed) · 1 unverified","official":{"repos":["iduta/iresnet"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":"/paper/instance-aware-context-focused-and-memory","slug":"instance-aware-context-focused-and-memory","title":"Instance-aware, Context-focused, and Memory-efficient Weakly Supervised Object Detection","date":"2020-04-09","arxiv_id":"2004.04725","n_code_links":2,"syntology":{"ran":5,"of":5,"n_ran_checked":5,"n_instrument":0,"unverified":0,"pointer_only":0,"phrase":"5 ran (of which 0 constructed an object rather than computing a result; 5 with no instrument failure: 0 honoured, 0 violated, 5 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","official":{"repos":["NVlabs/wetectron"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"paper":"/paper/evolving-normalization-activation-layers","slug":"evolving-normalization-activation-layers","title":"Evolving Normalization-Activation Layers","date":"2020-04-06","arxiv_id":"2004.02967","n_code_links":8,"syntology":{"ran":3,"of":5,"n_ran_checked":0,"n_instrument":3,"unverified":2,"pointer_only":3,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 3 where Syntology's instrument failed) · 2 unverified","official":null}},{"paper":"/paper/objectnet-dataset-reanalysis-and-correction","slug":"objectnet-dataset-reanalysis-and-correction","title":"ObjectNet Dataset: Reanalysis and Correction","date":"2020-04-04","arxiv_id":"2004.02042","n_code_links":1,"syntology":{"ran":1,"of":1,"n_ran_checked":0,"n_instrument":1,"unverified":0,"pointer_only":1,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","official":{"repos":["aliborji/ObjectNetReanalysis"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":"/paper/milking-cowmask-for-semi-supervised-image","slug":"milking-cowmask-for-semi-supervised-image","title":"Milking CowMask for Semi-Supervised Image Classification","date":"2020-03-26","arxiv_id":"2003.12022","n_code_links":2,"syntology":{"ran":1,"of":2,"n_ran_checked":1,"n_instrument":0,"unverified":1,"pointer_only":0,"phrase":"1 ran (of which 1 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified; the one sample that ran constructed an object rather than computing a result","official":{"repos":["google-research/google-research"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":1,"n_ran_no_instrument_failure":1,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":"/paper/meta-pseudo-labels","slug":"meta-pseudo-labels","title":"Meta Pseudo Labels","date":"2020-03-23","arxiv_id":"2003.10580","n_code_links":9,"syntology":{"ran":12,"of":14,"n_ran_checked":10,"n_instrument":2,"unverified":2,"pointer_only":3,"phrase":"12 ran (of which 0 constructed an object rather than computing a result; 10 with no instrument failure: 0 honoured, 0 violated, 10 with no contract checked; 2 where Syntology's instrument failed) · 2 unverified","official":{"repos":["google-research/google-research"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"paper":"/paper/metric-learning-cross-entropy-vs-pairwise","slug":"metric-learning-cross-entropy-vs-pairwise","title":"A unifying mutual information view of metric learning: cross-entropy vs. pairwise losses","date":"2020-03-19","arxiv_id":"2003.08983","n_code_links":1,"syntology":{"ran":1,"of":1,"n_ran_checked":1,"n_instrument":0,"unverified":0,"pointer_only":0,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 1 violated, 0 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","official":{"repos":["jeromerony/dml_cross_entropy"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":"/paper/rethinking-image-mixture-for-unsupervised","slug":"rethinking-image-mixture-for-unsupervised","title":"Un-Mix: Rethinking Image Mixtures for Unsupervised Visual Representation Learning","date":"2020-03-11","arxiv_id":"2003.05438","n_code_links":3,"syntology":{"ran":3,"of":4,"n_ran_checked":0,"n_instrument":3,"unverified":1,"pointer_only":4,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 3 where Syntology's instrument failed) · 1 unverified","official":{"repos":["szq0214/Rethinking-Image-Mixture-for-Unsupervised-Learning","szq0214/un-mix"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":"/paper/improved-baselines-with-momentum-contrastive","slug":"improved-baselines-with-momentum-contrastive","title":"Improved Baselines with Momentum Contrastive Learning","date":"2020-03-09","arxiv_id":"2003.04297","n_code_links":36,"syntology":{"ran":28,"of":43,"n_ran_checked":21,"n_instrument":7,"unverified":15,"pointer_only":15,"phrase":"28 ran (of which 0 constructed an object rather than computing a result; 21 with no instrument failure: 0 honoured, 1 violated, 20 with no contract checked; 7 where Syntology's instrument failed) · 15 unverified","official":{"repos":["facebookresearch/moco"],"state":"official: no sample here; runs from other or unrecorded repositories","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed","unlocated"]}}},{"paper":"/paper/salsanext-fast-semantic-segmentation-of-lidar","slug":"salsanext-fast-semantic-segmentation-of-lidar","title":"SalsaNext: Fast, Uncertainty-aware Semantic Segmentation of LiDAR Point Clouds for Autonomous Driving","date":"2020-03-07","arxiv_id":"2003.03653","n_code_links":5,"syntology":{"ran":8,"of":11,"n_ran_checked":4,"n_instrument":4,"unverified":3,"pointer_only":1,"phrase":"8 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 0 violated, 4 with no contract checked; 4 where Syntology's instrument failed) · 3 unverified","official":{"repos":["TiagoCortinhal/SalsaNext"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":2,"ran_from_kinds":["listed","official","unlocated"]}}},{"paper":"/paper/good-subnetworks-provably-exist-pruning-via","slug":"good-subnetworks-provably-exist-pruning-via","title":"Good Subnetworks Provably Exist: Pruning via Greedy Forward Selection","date":"2020-03-03","arxiv_id":"2003.01794","n_code_links":1,"syntology":{"ran":4,"of":7,"n_ran_checked":2,"n_instrument":2,"unverified":3,"pointer_only":7,"phrase":"4 ran (of which 1 constructed an object rather than computing a result; 2 with no instrument failure: 1 honoured, 0 violated, 1 with no contract checked; 2 where Syntology's instrument failed) · 3 unverified","official":{"repos":["lushleaf/Network-Pruning-Greedy-Forward-Selection"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":1,"n_ran_no_instrument_failure":2,"n_unverified":3,"ran_from_kinds":["official"]}}},{"paper":"/paper/understanding-and-enhancing-mixed-sample-data","slug":"understanding-and-enhancing-mixed-sample-data","title":"FMix: Enhancing Mixed Sample Data Augmentation","date":"2020-02-27","arxiv_id":"2002.12047","n_code_links":5,"syntology":{"ran":8,"of":8,"n_ran_checked":1,"n_instrument":7,"unverified":0,"pointer_only":3,"phrase":"8 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 1 honoured, 0 violated, 0 with no contract checked; 7 where Syntology's instrument failed) · 0 unverified","official":{"repos":["ecs-vlc/FMix"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["listed","official","unlocated"]}}},{"paper":"/paper/invariance-vs-robustness-of-neural-networks-1","slug":"invariance-vs-robustness-of-neural-networks-1","title":"Can we have it all? On the Trade-off between Spatial and Adversarial Robustness of Neural Networks","date":"2020-02-26","arxiv_id":"2002.11318","n_code_links":1,"syntology":{"ran":3,"of":4,"n_ran_checked":0,"n_instrument":3,"unverified":1,"pointer_only":3,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 3 where Syntology's instrument failed) · 1 unverified","official":{"repos":["ksandeshk/spatial-vs-robustness"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":"/paper/on-feature-normalization-and-data","slug":"on-feature-normalization-and-data","title":"On Feature Normalization and Data Augmentation","date":"2020-02-25","arxiv_id":"2002.11102","n_code_links":1,"syntology":{"ran":6,"of":14,"n_ran_checked":3,"n_instrument":3,"unverified":8,"pointer_only":2,"phrase":"6 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 3 where Syntology's instrument failed) · 8 unverified","official":{"repos":["Boyiliee/MoEx"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":8,"ran_from_kinds":["official"]}}},{"paper":"/paper/knapsack-pruning-with-inner-distillation","slug":"knapsack-pruning-with-inner-distillation","title":"Knapsack Pruning with Inner Distillation","date":"2020-02-19","arxiv_id":"2002.08258","n_code_links":1,"syntology":{"ran":3,"of":3,"n_ran_checked":0,"n_instrument":3,"unverified":0,"pointer_only":0,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 3 where Syntology's instrument failed) · 0 unverified","official":{"repos":["yoniaflalo/knapsack_pruning"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":"/paper/picking-winning-tickets-before-training-by-1","slug":"picking-winning-tickets-before-training-by-1","title":"Picking Winning Tickets Before Training by Preserving Gradient Flow","date":"2020-02-18","arxiv_id":"2002.07376","n_code_links":3,"syntology":{"ran":1,"of":2,"n_ran_checked":0,"n_instrument":1,"unverified":1,"pointer_only":0,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 1 unverified","official":{"repos":["alecwangcq/GraSP"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":"/paper/active-bayesian-assessment-for-black-box","slug":"active-bayesian-assessment-for-black-box","title":"Active Bayesian Assessment for Black-Box Classifiers","date":"2020-02-16","arxiv_id":"2002.06532","n_code_links":1,"syntology":{"ran":3,"of":3,"n_ran_checked":0,"n_instrument":3,"unverified":0,"pointer_only":0,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 3 where Syntology's instrument failed) · 0 unverified","official":{"repos":["disiji/bayesian-blackbox"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":"/paper/skip-connections-matter-on-the","slug":"skip-connections-matter-on-the","title":"Skip Connections Matter: On the Transferability of Adversarial Examples Generated with ResNets","date":"2020-02-14","arxiv_id":"2002.05990","n_code_links":4,"syntology":{"ran":4,"of":9,"n_ran_checked":1,"n_instrument":3,"unverified":5,"pointer_only":0,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 3 where Syntology's instrument failed) · 5 unverified","official":{"repos":["csdongxian/skip-connections-matter"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":2,"ran_from_kinds":["listed","official"]}}},{"paper":"/paper/a-simple-framework-for-contrastive-learning","slug":"a-simple-framework-for-contrastive-learning","title":"A Simple Framework for Contrastive Learning of Visual Representations","date":"2020-02-13","arxiv_id":"2002.05709","n_code_links":96,"syntology":{"ran":115,"of":137,"n_ran_checked":90,"n_instrument":25,"unverified":22,"pointer_only":52,"phrase":"115 ran (of which 33 constructed an object rather than computing a result; 90 with no instrument failure: 1 honoured, 1 violated, 88 with no contract checked; 25 where Syntology's instrument failed) · 22 unverified","official":{"repos":["google-research/simclr"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed","official"]}}},{"paper":"/paper/cross-iteration-batch-normalization","slug":"cross-iteration-batch-normalization","title":"Cross-Iteration Batch Normalization","date":"2020-02-13","arxiv_id":"2002.05712","n_code_links":2,"syntology":{"ran":4,"of":6,"n_ran_checked":4,"n_instrument":0,"unverified":2,"pointer_only":1,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 0 violated, 4 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified","official":{"repos":["Howal/Cross-iterationBatchNorm"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"paper":"/paper/lookahead-a-far-sighted-alternative-of-1","slug":"lookahead-a-far-sighted-alternative-of-1","title":"Lookahead: a Far-Sighted Alternative of Magnitude-based Pruning","date":"2020-02-12","arxiv_id":"2002.04809","n_code_links":1,"syntology":{"ran":8,"of":10,"n_ran_checked":6,"n_instrument":2,"unverified":2,"pointer_only":10,"phrase":"8 ran (of which 0 constructed an object rather than computing a result; 6 with no instrument failure: 6 honoured, 0 violated, 0 with no contract checked; 2 where Syntology's instrument failed) · 2 unverified","official":{"repos":["alinlab/lookahead_pruning"],"state":"official (archive's flag): 8 ran","n_ran":8,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":2,"ran_from_kinds":["official"]}}},{"paper":"/paper/the-devil-is-in-the-channels-mutual-channel","slug":"the-devil-is-in-the-channels-mutual-channel","title":"The Devil is in the Channels: Mutual-Channel Loss for Fine-Grained Image Classification","date":"2020-02-11","arxiv_id":"2002.04264","n_code_links":3,"syntology":{"ran":4,"of":5,"n_ran_checked":3,"n_instrument":1,"unverified":1,"pointer_only":2,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 1 where Syntology's instrument failed) · 1 unverified","official":{"repos":["dongliangchang/Mutual-Channel-Loss"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":1,"ran_from_kinds":["listed","official"]}}},{"paper":"/paper/compounding-the-performance-improvements-of","slug":"compounding-the-performance-improvements-of","title":"Compounding the Performance Improvements of Assembled Techniques in a Convolutional Neural Network","date":"2020-01-17","arxiv_id":"2001.06268","n_code_links":1,"syntology":{"ran":3,"of":11,"n_ran_checked":2,"n_instrument":1,"unverified":8,"pointer_only":0,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 1 where Syntology's instrument failed) · 8 unverified","official":{"repos":["clovaai/assembled-cnn"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":8,"ran_from_kinds":["official"]}}},{"paper":"/paper/deep-residual-flow-for-novelty-detection","slug":"deep-residual-flow-for-novelty-detection","title":"Deep Residual Flow for Out of Distribution Detection","date":"2020-01-15","arxiv_id":"2001.05419","n_code_links":1,"syntology":{"ran":1,"of":2,"n_ran_checked":0,"n_instrument":1,"unverified":1,"pointer_only":2,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 1 unverified","official":{"repos":["EvZissel/Residual-Flow"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":"/paper/sparse-weight-activation-training-1","slug":"sparse-weight-activation-training-1","title":"Sparse Weight Activation Training","date":"2020-01-07","arxiv_id":"2001.01969","n_code_links":1,"syntology":{"ran":3,"of":4,"n_ran_checked":3,"n_instrument":0,"unverified":1,"pointer_only":4,"phrase":"3 ran (of which 3 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified; every one of the 3 samples that ran constructed an object rather than computing a result","official":{"repos":["AamirRaihan/SWAT"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":3,"n_ran_no_instrument_failure":3,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":"/paper/mutual-mean-teaching-pseudo-label-refinery-1","slug":"mutual-mean-teaching-pseudo-label-refinery-1","title":"Mutual Mean-Teaching: Pseudo Label Refinery for Unsupervised Domain Adaptation on Person Re-identification","date":"2020-01-06","arxiv_id":"2001.01526","n_code_links":2,"syntology":{"ran":8,"of":8,"n_ran_checked":2,"n_instrument":6,"unverified":0,"pointer_only":0,"phrase":"8 ran (of which 2 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 6 where Syntology's instrument failed) · 0 unverified","official":{"repos":["yxgeee/MMT"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":1,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["listed","official"]}}},{"paper":"/paper/pac-confidence-sets-for-deep-neural-networks-1","slug":"pac-confidence-sets-for-deep-neural-networks-1","title":"PAC Confidence Sets for Deep Neural Networks via Calibrated Prediction","date":"2019-12-31","arxiv_id":"2001.00106","n_code_links":2,"syntology":{"ran":7,"of":11,"n_ran_checked":7,"n_instrument":0,"unverified":4,"pointer_only":0,"phrase":"7 ran (of which 0 constructed an object rather than computing a result; 7 with no instrument failure: 0 honoured, 0 violated, 7 with no contract checked; 0 where Syntology's instrument failed) · 4 unverified","official":{"repos":["sangdon/PAC-confidence-set"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":0,"n_ran_no_instrument_failure":7,"n_unverified":4,"ran_from_kinds":["official"]}}},{"paper":"/paper/large-scale-learning-of-general-visual","slug":"large-scale-learning-of-general-visual","title":"Big Transfer (BiT): General Visual Representation Learning","date":"2019-12-24","arxiv_id":"1912.11370","n_code_links":9,"syntology":{"ran":9,"of":10,"n_ran_checked":7,"n_instrument":2,"unverified":1,"pointer_only":0,"phrase":"9 ran (of which 0 constructed an object rather than computing a result; 7 with no instrument failure: 0 honoured, 1 violated, 6 with no contract checked; 2 where Syntology's instrument failed) · 1 unverified","official":{"repos":["google-research/big_transfer"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"paper":"/paper/bridging-the-gap-between-anchor-based-and","slug":"bridging-the-gap-between-anchor-based-and","title":"Bridging the Gap Between Anchor-based and Anchor-free Detection via Adaptive Training Sample Selection","date":"2019-12-05","arxiv_id":"1912.02424","n_code_links":13,"syntology":{"ran":4,"of":4,"n_ran_checked":4,"n_instrument":0,"unverified":0,"pointer_only":0,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 0 violated, 4 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","official":{"repos":["sfzhang15/ATSS"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"paper":"/paper/augmix-a-simple-data-processing-method-to","slug":"augmix-a-simple-data-processing-method-to","title":"AugMix: A Simple Data Processing Method to Improve Robustness and Uncertainty","date":"2019-12-05","arxiv_id":"1912.02781","n_code_links":15,"syntology":{"ran":46,"of":51,"n_ran_checked":9,"n_instrument":37,"unverified":5,"pointer_only":25,"phrase":"46 ran (of which 0 constructed an object rather than computing a result; 9 with no instrument failure: 4 honoured, 2 violated, 3 with no contract checked; 37 where Syntology's instrument failed) · 5 unverified","official":{"repos":["google-research/augmix"],"state":"official (archive's flag): 12 ran","n_ran":12,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed","official","unlocated"]}}},{"paper":"/paper/self-supervised-learning-of-pretext-invariant","slug":"self-supervised-learning-of-pretext-invariant","title":"Self-Supervised Learning of Pretext-Invariant Representations","date":"2019-12-04","arxiv_id":"1912.01991","n_code_links":7,"syntology":{"ran":3,"of":4,"n_ran_checked":3,"n_instrument":0,"unverified":1,"pointer_only":4,"phrase":"3 ran (of which 3 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified; every one of the 3 samples that ran constructed an object rather than computing a result","official":null}},{"paper":"/paper/yolact-better-real-time-instance-segmentation","slug":"yolact-better-real-time-instance-segmentation","title":"YOLACT++: Better Real-time Instance Segmentation","date":"2019-12-03","arxiv_id":"1912.06218","n_code_links":36,"syntology":{"ran":37,"of":43,"n_ran_checked":33,"n_instrument":4,"unverified":6,"pointer_only":5,"phrase":"37 ran (of which 0 constructed an object rather than computing a result; 33 with no instrument failure: 2 honoured, 2 violated, 29 with no contract checked; 4 where Syntology's instrument failed) · 6 unverified","official":{"repos":["dbolya/yolact"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":1,"ran_from_kinds":["listed","official"]}}},{"paper":"/paper/logan-latent-optimisation-for-generative-1","slug":"logan-latent-optimisation-for-generative-1","title":"LOGAN: Latent Optimisation for Generative Adversarial Networks","date":"2019-12-02","arxiv_id":"1912.00953","n_code_links":1,"syntology":{"ran":5,"of":8,"n_ran_checked":4,"n_instrument":1,"unverified":3,"pointer_only":2,"phrase":"5 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 1 violated, 3 with no contract checked; 1 where Syntology's instrument failed) · 3 unverified","official":null}},{"paper":"/paper/whats-hidden-in-a-randomly-weighted-neural","slug":"whats-hidden-in-a-randomly-weighted-neural","title":"What's Hidden in a Randomly Weighted Neural Network?","date":"2019-11-29","arxiv_id":"1911.13299","n_code_links":4,"syntology":{"ran":9,"of":9,"n_ran_checked":8,"n_instrument":1,"unverified":0,"pointer_only":5,"phrase":"9 ran (of which 0 constructed an object rather than computing a result; 8 with no instrument failure: 0 honoured, 0 violated, 8 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","official":{"repos":["allenai/hidden-networks"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":0,"ran_from_kinds":["listed","official"]}}},{"paper":"/paper/ghostnet-more-features-from-cheap-operations","slug":"ghostnet-more-features-from-cheap-operations","title":"GhostNet: More Features from Cheap Operations","date":"2019-11-27","arxiv_id":"1911.11907","n_code_links":33,"syntology":{"ran":19,"of":23,"n_ran_checked":16,"n_instrument":3,"unverified":4,"pointer_only":5,"phrase":"19 ran (of which 0 constructed an object rather than computing a result; 16 with no instrument failure: 2 honoured, 0 violated, 14 with no contract checked; 3 where Syntology's instrument failed) · 4 unverified","official":{"repos":["huawei-noah/ghostnet"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"paper":"/paper/filter-response-normalization-layer","slug":"filter-response-normalization-layer","title":"Filter Response Normalization Layer: Eliminating Batch Dependence in the Training of Deep Neural Networks","date":"2019-11-21","arxiv_id":"1911.09737","n_code_links":16,"syntology":{"ran":2,"of":2,"n_ran_checked":0,"n_instrument":2,"unverified":0,"pointer_only":0,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 2 where Syntology's instrument failed) · 0 unverified","official":null}},{"paper":"/paper/real-time-scene-text-detection-with","slug":"real-time-scene-text-detection-with","title":"Real-time Scene Text Detection with Differentiable Binarization","date":"2019-11-20","arxiv_id":"1911.08947","n_code_links":15,"syntology":{"ran":20,"of":25,"n_ran_checked":17,"n_instrument":3,"unverified":5,"pointer_only":1,"phrase":"20 ran (of which 0 constructed an object rather than computing a result; 17 with no instrument failure: 0 honoured, 0 violated, 17 with no contract checked; 3 where Syntology's instrument failed) · 5 unverified","official":{"repos":["MhLiao/DB"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"paper":"/paper/centermask-real-time-anchor-free-instance-1","slug":"centermask-real-time-anchor-free-instance-1","title":"CenterMask : Real-Time Anchor-Free Instance Segmentation","date":"2019-11-15","arxiv_id":"1911.06667","n_code_links":8,"syntology":{"ran":2,"of":2,"n_ran_checked":2,"n_instrument":0,"unverified":0,"pointer_only":2,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 1 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","official":{"repos":["youngwanLEE/CenterMask"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["listed","official"]}}},{"paper":"/paper/momentum-contrast-for-unsupervised-visual","slug":"momentum-contrast-for-unsupervised-visual","title":"Momentum Contrast for Unsupervised Visual Representation Learning","date":"2019-11-13","arxiv_id":"1911.05722","n_code_links":44,"syntology":{"ran":28,"of":42,"n_ran_checked":23,"n_instrument":5,"unverified":14,"pointer_only":19,"phrase":"28 ran (of which 16 constructed an object rather than computing a result; 23 with no instrument failure: 0 honoured, 0 violated, 23 with no contract checked; 5 where Syntology's instrument failed) · 14 unverified","official":{"repos":["facebookresearch/moco","ppwwyyxx/moco.tensorflow"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"paper":"/paper/self-correction-for-human-parsing","slug":"self-correction-for-human-parsing","title":"Self-Correction for Human Parsing","date":"2019-10-22","arxiv_id":"1910.09777","n_code_links":2,"syntology":{"ran":3,"of":3,"n_ran_checked":3,"n_instrument":0,"unverified":0,"pointer_only":0,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 1 honoured, 1 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","official":{"repos":["PeikeLi/Self-Correction-Human-Parsing"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":0,"ran_from_kinds":["listed","official"]}}},{"paper":"/paper/on-the-adequacy-of-untuned-warmup-for","slug":"on-the-adequacy-of-untuned-warmup-for","title":"On the adequacy of untuned warmup for adaptive optimization","date":"2019-10-09","arxiv_id":"1910.04209","n_code_links":1,"syntology":{"ran":4,"of":4,"n_ran_checked":4,"n_instrument":0,"unverified":0,"pointer_only":0,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 0 violated, 4 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","official":null}},{"paper":"/paper/eca-net-efficient-channel-attention-for-deep","slug":"eca-net-efficient-channel-attention-for-deep","title":"ECA-Net: Efficient Channel Attention for Deep Convolutional Neural Networks","date":"2019-10-08","arxiv_id":"1910.03151","n_code_links":13,"syntology":{"ran":3,"of":8,"n_ran_checked":2,"n_instrument":1,"unverified":5,"pointer_only":1,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 1 where Syntology's instrument failed) · 5 unverified","official":{"repos":["BangguWu/ECANet"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":5,"ran_from_kinds":["official"]}}},{"paper":"/paper/the-visual-task-adaptation-benchmark","slug":"the-visual-task-adaptation-benchmark","title":"A Large-scale Study of Representation Learning with the Visual Task Adaptation Benchmark","date":"2019-10-01","arxiv_id":"1910.04867","n_code_links":2,"syntology":{"ran":1,"of":1,"n_ran_checked":0,"n_instrument":1,"unverified":0,"pointer_only":0,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","official":{"repos":["google-research/task_adaptation"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":"/paper/randaugment-practical-data-augmentation-with","slug":"randaugment-practical-data-augmentation-with","title":"RandAugment: Practical automated data augmentation with a reduced search space","date":"2019-09-30","arxiv_id":"1909.13719","n_code_links":19,"syntology":{"ran":58,"of":65,"n_ran_checked":7,"n_instrument":51,"unverified":7,"pointer_only":17,"phrase":"58 ran (of which 1 constructed an object rather than computing a result; 7 with no instrument failure: 0 honoured, 1 violated, 6 with no contract checked; 51 where Syntology's instrument failed) · 7 unverified","official":null}},{"paper":"/paper/polarmask-single-shot-instance-segmentation","slug":"polarmask-single-shot-instance-segmentation","title":"PolarMask: Single Shot Instance Segmentation with Polar Representation","date":"2019-09-29","arxiv_id":"1909.13226","n_code_links":2,"syntology":{"ran":1,"of":1,"n_ran_checked":1,"n_instrument":0,"unverified":0,"pointer_only":0,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","official":{"repos":["xieenze/PolarMask"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":"/paper/object-contextual-representations-for","slug":"object-contextual-representations-for","title":"Segmentation Transformer: Object-Contextual Representations for Semantic Segmentation","date":"2019-09-24","arxiv_id":"1909.11065","n_code_links":11,"syntology":{"ran":5,"of":9,"n_ran_checked":1,"n_instrument":4,"unverified":4,"pointer_only":1,"phrase":"5 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 4 where Syntology's instrument failed) · 4 unverified","official":{"repos":["HRNet/HRNet-Semantic-Segmentation"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed","official"]}}},{"paper":"/paper/video-representation-learning-by-dense","slug":"video-representation-learning-by-dense","title":"Video Representation Learning by Dense Predictive Coding","date":"2019-09-10","arxiv_id":"1909.04656","n_code_links":1,"syntology":{"ran":9,"of":11,"n_ran_checked":8,"n_instrument":1,"unverified":2,"pointer_only":0,"phrase":"9 ran (of which 0 constructed an object rather than computing a result; 8 with no instrument failure: 0 honoured, 0 violated, 8 with no contract checked; 1 where Syntology's instrument failed) · 2 unverified","official":{"repos":["TengdaHan/DPC"],"state":"official (archive's flag): 9 ran","n_ran":9,"n_constructed":0,"n_ran_no_instrument_failure":8,"n_unverified":2,"ran_from_kinds":["official"]}}},{"paper":"/paper/cbnet-a-novel-composite-backbone-network","slug":"cbnet-a-novel-composite-backbone-network","title":"CBNet: A Novel Composite Backbone Network Architecture for Object Detection","date":"2019-09-09","arxiv_id":"1909.03625","n_code_links":6,"syntology":{"ran":2,"of":4,"n_ran_checked":2,"n_instrument":0,"unverified":2,"pointer_only":1,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified","official":{"repos":["PKUbahuangliuhe/CBNet"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":"/paper/freeanchor-learning-to-match-anchors-for","slug":"freeanchor-learning-to-match-anchors-for","title":"FreeAnchor: Learning to Match Anchors for Visual Object Detection","date":"2019-09-05","arxiv_id":"1909.02466","n_code_links":4,"syntology":{"ran":3,"of":3,"n_ran_checked":0,"n_instrument":3,"unverified":0,"pointer_only":0,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 3 where Syntology's instrument failed) · 0 unverified","official":{"repos":["zhangxiaosong18/FreeAnchor"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":"/paper/confidence-regularized-self-training","slug":"confidence-regularized-self-training","title":"Confidence Regularized Self-Training","date":"2019-08-26","arxiv_id":"1908.09822","n_code_links":2,"syntology":{"ran":1,"of":1,"n_ran_checked":0,"n_instrument":1,"unverified":0,"pointer_only":1,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","official":{"repos":["yzou2/CRST"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":"/paper/mish-a-self-regularized-non-monotonic-neural","slug":"mish-a-self-regularized-non-monotonic-neural","title":"Mish: A Self Regularized Non-Monotonic Activation Function","date":"2019-08-23","arxiv_id":"1908.08681","n_code_links":9,"syntology":{"ran":9,"of":12,"n_ran_checked":8,"n_instrument":1,"unverified":3,"pointer_only":1,"phrase":"9 ran (of which 0 constructed an object rather than computing a result; 8 with no instrument failure: 1 honoured, 0 violated, 7 with no contract checked; 1 where Syntology's instrument failed) · 3 unverified","official":{"repos":["digantamisra98/Mish"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":3,"ran_from_kinds":["listed","official"]}}},{"paper":"/paper/190807919","slug":"190807919","title":"Deep High-Resolution Representation Learning for Visual Recognition","date":"2019-08-20","arxiv_id":"1908.07919","n_code_links":42,"syntology":{"ran":21,"of":34,"n_ran_checked":19,"n_instrument":2,"unverified":13,"pointer_only":21,"phrase":"21 ran (of which 0 constructed an object rather than computing a result; 19 with no instrument failure: 0 honoured, 1 violated, 18 with no contract checked; 2 where Syntology's instrument failed) · 13 unverified","official":null}},{"paper":"/paper/abd-net-attentive-but-diverse-person-re","slug":"abd-net-attentive-but-diverse-person-re","title":"ABD-Net: Attentive but Diverse Person Re-Identification","date":"2019-08-03","arxiv_id":"1908.01114","n_code_links":4,"syntology":{"ran":8,"of":9,"n_ran_checked":8,"n_instrument":0,"unverified":1,"pointer_only":1,"phrase":"8 ran (of which 0 constructed an object rather than computing a result; 8 with no instrument failure: 0 honoured, 0 violated, 8 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","official":{"repos":["TAMU-VITA/ABD-Net"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":1,"ran_from_kinds":["listed","official"]}}},{"paper":"/paper/learning-lightweight-lane-detection-cnns-by","slug":"learning-lightweight-lane-detection-cnns-by","title":"Learning Lightweight Lane Detection CNNs by Self Attention Distillation","date":"2019-08-02","arxiv_id":"1908.00821","n_code_links":2,"syntology":{"ran":7,"of":8,"n_ran_checked":5,"n_instrument":2,"unverified":1,"pointer_only":1,"phrase":"7 ran (of which 0 constructed an object rather than computing a result; 5 with no instrument failure: 0 honoured, 0 violated, 5 with no contract checked; 2 where Syntology's instrument failed) · 1 unverified","official":{"repos":["cardwing/Codes-for-Lane-Detection"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":1,"ran_from_kinds":["listed","official"]}}},{"paper":"/paper/natural-adversarial-examples","slug":"natural-adversarial-examples","title":"Natural Adversarial Examples","date":"2019-07-16","arxiv_id":"1907.07174","n_code_links":3,"syntology":{"ran":4,"of":4,"n_ran_checked":3,"n_instrument":1,"unverified":0,"pointer_only":1,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","official":{"repos":["hendrycks/natural-adv-examples"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":"/paper/large-scale-adversarial-representation","slug":"large-scale-adversarial-representation","title":"Large Scale Adversarial Representation Learning","date":"2019-07-04","arxiv_id":"1907.02544","n_code_links":4,"syntology":{"ran":2,"of":3,"n_ran_checked":2,"n_instrument":0,"unverified":1,"pointer_only":0,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","official":null}},{"paper":"/paper/neural-odes-as-the-deep-limit-of-resnets-with","slug":"neural-odes-as-the-deep-limit-of-resnets-with","title":"Neural ODEs as the Deep Limit of ResNets with constant weights","date":"2019-06-28","arxiv_id":"1906.12183","n_code_links":2,"syntology":{"ran":5,"of":5,"n_ran_checked":2,"n_instrument":3,"unverified":0,"pointer_only":5,"phrase":"5 ran (of which 2 constructed an object rather than computing a result; 2 with no instrument failure: 2 honoured, 0 violated, 0 with no contract checked; 3 where Syntology's instrument failed) · 0 unverified","official":null}},{"paper":"/paper/using-self-supervised-learning-can-improve","slug":"using-self-supervised-learning-can-improve","title":"Using Self-Supervised Learning Can Improve Model Robustness and Uncertainty","date":"2019-06-28","arxiv_id":"1906.12340","n_code_links":4,"syntology":{"ran":11,"of":12,"n_ran_checked":6,"n_instrument":5,"unverified":1,"pointer_only":4,"phrase":"11 ran (of which 0 constructed an object rather than computing a result; 6 with no instrument failure: 0 honoured, 0 violated, 6 with no contract checked; 5 where Syntology's instrument failed) · 1 unverified","official":{"repos":["hendrycks/ss-ood"],"state":"official (archive's flag): 11 ran","n_ran":11,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":"/paper/learning-data-augmentation-strategies-for","slug":"learning-data-augmentation-strategies-for","title":"Learning Data Augmentation Strategies for Object Detection","date":"2019-06-26","arxiv_id":"1906.11172","n_code_links":6,"syntology":{"ran":3,"of":3,"n_ran_checked":1,"n_instrument":2,"unverified":0,"pointer_only":3,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 1 violated, 0 with no contract checked; 2 where Syntology's instrument failed) · 0 unverified","official":{"repos":["tensorflow/tpu"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"paper":"/paper/contrastive-multiview-coding","slug":"contrastive-multiview-coding","title":"Contrastive Multiview Coding","date":"2019-06-13","arxiv_id":"1906.05849","n_code_links":8,"syntology":{"ran":4,"of":4,"n_ran_checked":2,"n_instrument":2,"unverified":0,"pointer_only":2,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 2 where Syntology's instrument failed) · 0 unverified","official":{"repos":["HobbitLong/CMC"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed","official"]}}},{"paper":"/paper/stand-alone-self-attention-in-vision-models","slug":"stand-alone-self-attention-in-vision-models","title":"Stand-Alone Self-Attention in Vision Models","date":"2019-06-13","arxiv_id":"1906.05909","n_code_links":8,"syntology":{"ran":2,"of":3,"n_ran_checked":1,"n_instrument":1,"unverified":1,"pointer_only":1,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 1 where Syntology's instrument failed) · 1 unverified","official":{"repos":["google-research/google-research"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}}],"record_sha256":"c2b0fe5050fa61fb7c4d078cd2309b84204d22c2b0f2e51f14e9881657601c91","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}