{"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/feedforward-network/papers/12","list_of":"/method/feedforward-network","method":"Feedforward Network","archive":{"snapshot":"2025-07-28"},"syntology_read_at":"2026-09-28T10:30:06+00:00","order":"archive","order_definition":"date (newest first), then slug","page":12,"pages_in_order":14,"rows_per_page":100,"rows":[1101,1200],"of":1339,"counts":{"archive_papers_tagged":1339,"with_a_code_link":683,"where_syntology_ran_a_sample":233,"not_listed_spam_title":0,"listed":1339,"listed_where_code_ran":233,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":204,"every_run_a_failure_of_syntologys_instrument":29,"listed_with_a_run_with_no_instrument_failure":204,"listed_every_run_a_failure_of_syntologys_instrument":29,"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/feedforward-network","prev":"/method/feedforward-network/papers/11","next":"/method/feedforward-network/papers/13","papers":[{"paper":"/paper/smyrf-efficient-attention-using-asymmetric-1","slug":"smyrf-efficient-attention-using-asymmetric-1","title":"SMYRF - Efficient Attention using Asymmetric Clustering","date":"2020-12-01","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":"/paper/self-supervised-contrastive-learning-for-2","slug":"self-supervised-contrastive-learning-for-2","title":"Self supervised contrastive learning for digital histopathology","date":"2020-11-27","arxiv_id":"2011.13971","n_code_links":2,"syntology":null},{"paper":"/paper/tstarbot-x-an-open-sourced-and-comprehensive","slug":"tstarbot-x-an-open-sourced-and-comprehensive","title":"TStarBot-X: An Open-Sourced and Comprehensive Study for Efficient League Training in StarCraft II Full Game","date":"2020-11-27","arxiv_id":"2011.13729","n_code_links":1,"syntology":null},{"paper":null,"slug":"beyond-single-instance-multi-view","title":"A Unified Mixture-View Framework for Unsupervised Representation Learning","date":"2020-11-26","arxiv_id":"2011.13356","n_code_links":0,"syntology":null},{"paper":"/paper/omni-gan-on-the-secrets-of-cgans-and-beyond","slug":"omni-gan-on-the-secrets-of-cgans-and-beyond","title":"Omni-GAN: On the Secrets of cGANs and Beyond","date":"2020-11-26","arxiv_id":"2011.13074","n_code_links":3,"syntology":null},{"paper":"/paper/exploring-contrastive-learning-in-human","slug":"exploring-contrastive-learning-in-human","title":"Exploring Contrastive Learning in Human Activity Recognition for Healthcare","date":"2020-11-23","arxiv_id":"2011.11542","n_code_links":1,"syntology":null},{"paper":"/paper/histogan-controlling-colors-of-gan-generated","slug":"histogan-controlling-colors-of-gan-generated","title":"HistoGAN: Controlling Colors of GAN-Generated and Real Images via Color Histograms","date":"2020-11-23","arxiv_id":"2011.11731","n_code_links":1,"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":["mahmoudnafifi/HistoGAN"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"deep-learning-model-trained-on-mobile-phone","title":"Deep learning model trained on mobile phone-acquired frozen section images effectively detects basal cell carcinoma","date":"2020-11-22","arxiv_id":"2011.11081","n_code_links":0,"syntology":null},{"paper":"/paper/rethinking-transformer-based-set-prediction","slug":"rethinking-transformer-based-set-prediction","title":"Rethinking Transformer-based Set Prediction for Object Detection","date":"2020-11-21","arxiv_id":"2011.10881","n_code_links":1,"syntology":{"ran":4,"of":4,"n_ran_checked":3,"n_instrument":1,"unverified":0,"pointer_only":0,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 3 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","official":{"repos":["edward-sun/tsp-detection"],"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":null,"slug":"deep-lf-net-semantic-lung-segmentation-from","title":"Deep LF-Net: Semantic Lung Segmentation from Indian Chest Radiographs Including Severely Unhealthy Images","date":"2020-11-19","arxiv_id":"2011.09695","n_code_links":0,"syntology":null},{"paper":"/paper/adaptive-channel-estimation-based-on-deep","slug":"adaptive-channel-estimation-based-on-deep","title":"Adaptive Channel Estimation based on Deep Learning","date":"2020-11-18","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":"/paper/end-to-end-object-detection-with-adaptive","slug":"end-to-end-object-detection-with-adaptive","title":"End-to-End Object Detection with Adaptive Clustering Transformer","date":"2020-11-18","arxiv_id":"2011.09315","n_code_links":1,"syntology":null},{"paper":"/paper/up-detr-unsupervised-pre-training-for-object","slug":"up-detr-unsupervised-pre-training-for-object","title":"UP-DETR: Unsupervised Pre-training for Object Detection with Transformers","date":"2020-11-18","arxiv_id":"2011.09094","n_code_links":2,"syntology":null},{"paper":"/paper/deepi2i-enabling-deep-hierarchical-image-to","slug":"deepi2i-enabling-deep-hierarchical-image-to","title":"DeepI2I: Enabling Deep Hierarchical Image-to-Image Translation by Transferring from GANs","date":"2020-11-11","arxiv_id":"2011.05867","n_code_links":1,"syntology":null},{"paper":null,"slug":"towards-domain-agnostic-contrastive-learning","title":"Towards Domain-Agnostic Contrastive Learning","date":"2020-11-09","arxiv_id":"2011.04419","n_code_links":0,"syntology":null},{"paper":"/paper/disentangling-latent-space-for-unsupervised","slug":"disentangling-latent-space-for-unsupervised","title":"Towards Disentangling Latent Space for Unsupervised Semantic Face Editing","date":"2020-11-05","arxiv_id":"2011.02638","n_code_links":1,"syntology":null},{"paper":"/paper/intriguing-properties-of-contrastive-losses","slug":"intriguing-properties-of-contrastive-losses","title":"Intriguing Properties of Contrastive Losses","date":"2020-11-05","arxiv_id":"2011.02803","n_code_links":3,"syntology":null},{"paper":"/paper/transforming-facial-weight-of-real-images-by","slug":"transforming-facial-weight-of-real-images-by","title":"Transforming Facial Weight of Real Images by Editing Latent Space of StyleGAN","date":"2020-11-05","arxiv_id":"2011.02606","n_code_links":1,"syntology":null},{"paper":"/paper/learning-visual-representations-for-transfer-1","slug":"learning-visual-representations-for-transfer-1","title":"Learning Visual Representations for Transfer Learning by Suppressing Texture","date":"2020-11-03","arxiv_id":"2011.01901","n_code_links":1,"syntology":null},{"paper":null,"slug":"deep-representation-decomposition-for-feature","title":"Representation Decomposition for Image Manipulation and Beyond","date":"2020-11-02","arxiv_id":"2011.00788","n_code_links":0,"syntology":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":null,"slug":"dpd-infogan-differentially-private","title":"DPD-InfoGAN: Differentially Private Distributed InfoGAN","date":"2020-10-22","arxiv_id":"2010.11398","n_code_links":0,"syntology":null},{"paper":"/paper/neural-audio-fingerprint-for-high-specific","slug":"neural-audio-fingerprint-for-high-specific","title":"Neural Audio Fingerprint for High-specific Audio Retrieval based on Contrastive Learning","date":"2020-10-22","arxiv_id":"2010.11910","n_code_links":3,"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":["mimbres/neural-audio-fp"],"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":null,"slug":"task-adaptive-feature-transformer-for-few","title":"Task-Adaptive Feature Transformer for Few-Shot Segmentation","date":"2020-10-22","arxiv_id":"2010.11437","n_code_links":0,"syntology":null},{"paper":null,"slug":"2nd-place-solution-to-instance-segmentation","title":"2nd Place Solution to Instance Segmentation of IJCAI 3D AI Challenge 2020","date":"2020-10-21","arxiv_id":"2010.10957","n_code_links":0,"syntology":null},{"paper":"/paper/one-model-to-reconstruct-them-all-a-novel-way","slug":"one-model-to-reconstruct-them-all-a-novel-way","title":"One Model to Reconstruct Them All: A Novel Way to Use the Stochastic Noise in StyleGAN","date":"2020-10-21","arxiv_id":"2010.11113","n_code_links":1,"syntology":null},{"paper":"/paper/for-self-supervised-learning-rationality-1","slug":"for-self-supervised-learning-rationality-1","title":"For self-supervised learning, Rationality implies generalization, provably","date":"2020-10-16","arxiv_id":"2010.08508","n_code_links":2,"syntology":null},{"paper":null,"slug":"self-supervised-ranking-for-representation","title":"Self-Supervised Ranking for Representation Learning","date":"2020-10-14","arxiv_id":"2010.07258","n_code_links":0,"syntology":null},{"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":null,"slug":"are-all-negatives-created-equal-in-1","title":"Are all negatives created equal in contrastive instance discrimination?","date":"2020-10-13","arxiv_id":"2010.06682","n_code_links":0,"syntology":null},{"paper":null,"slug":"conditioning-trick-for-training-stable-gans-1","title":"Conditioning Trick for Training Stable GANs","date":"2020-10-12","arxiv_id":"2010.05844","n_code_links":0,"syntology":null},{"paper":"/paper/resolution-dependant-gan-interpolation-for","slug":"resolution-dependant-gan-interpolation-for","title":"Resolution Dependent GAN Interpolation for Controllable Image Synthesis Between Domains","date":"2020-10-11","arxiv_id":"2010.05334","n_code_links":3,"syntology":null},{"paper":"/paper/smyrf-efficient-attention-using-asymmetric","slug":"smyrf-efficient-attention-using-asymmetric","title":"SMYRF: Efficient Attention using Asymmetric Clustering","date":"2020-10-11","arxiv_id":"2010.05315","n_code_links":1,"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":["giannisdaras/smyrf"],"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":["unlocated"]}}},{"paper":"/paper/deformable-detr-deformable-transformers-for-1","slug":"deformable-detr-deformable-transformers-for-1","title":"Deformable DETR: Deformable Transformers for End-to-End Object Detection","date":"2020-10-08","arxiv_id":"2010.04159","n_code_links":20,"syntology":{"ran":37,"of":55,"n_ran_checked":24,"n_instrument":13,"unverified":18,"pointer_only":21,"phrase":"37 ran (of which 9 constructed an object rather than computing a result; 24 with no instrument failure: 1 honoured, 3 violated, 20 with no contract checked; 13 where Syntology's instrument failed) · 18 unverified","official":{"repos":["fundamentalvision/Deformable-DETR"],"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/logan-local-group-bias-detection-by","slug":"logan-local-group-bias-detection-by","title":"LOGAN: Local Group Bias Detection by Clustering","date":"2020-10-06","arxiv_id":"2010.02867","n_code_links":1,"syntology":null},{"paper":"/paper/eqco-equivalent-rules-for-self-supervised-1","slug":"eqco-equivalent-rules-for-self-supervised-1","title":"EqCo: Equivalent Rules for Self-supervised Contrastive Learning","date":"2020-10-05","arxiv_id":"2010.01929","n_code_links":1,"syntology":null},{"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/tinygan-distilling-biggan-for-conditional","slug":"tinygan-distilling-biggan-for-conditional","title":"TinyGAN: Distilling BigGAN for Conditional Image Generation","date":"2020-09-29","arxiv_id":"2009.13829","n_code_links":1,"syntology":null},{"paper":"/paper/g-simclr-self-supervised-contrastive-learning","slug":"g-simclr-self-supervised-contrastive-learning","title":"G-SimCLR: Self-Supervised Contrastive Learning with Guided Projection via Pseudo Labelling","date":"2020-09-28","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":"/paper/g-simclr-self-supervised-contrastive-learning-1","slug":"g-simclr-self-supervised-contrastive-learning-1","title":"G-SimCLR : Self-Supervised Contrastive Learning with Guided Projection via Pseudo Labelling","date":"2020-09-25","arxiv_id":"2009.12007","n_code_links":1,"syntology":null},{"paper":null,"slug":"pie-portrait-image-embedding-for-semantic","title":"PIE: Portrait Image Embedding for Semantic Control","date":"2020-09-20","arxiv_id":"2009.09485","n_code_links":0,"syntology":null},{"paper":"/paper/aag-self-supervised-representation-learning","slug":"aag-self-supervised-representation-learning","title":"AAG: Self-Supervised Representation Learning by Auxiliary Augmentation with GNT-Xent Loss","date":"2020-09-17","arxiv_id":"2009.07994","n_code_links":3,"syntology":null},{"paper":"/paper/towards-fine-grained-large-object","slug":"towards-fine-grained-large-object","title":"Towards Fine-grained Large Object Segmentation 1st Place Solution to 3D AI Challenge 2020 -- Instance Segmentation Track","date":"2020-09-10","arxiv_id":"2009.04650","n_code_links":1,"syntology":null},{"paper":null,"slug":"hsfm-s-nn-combining-a-feedforward-motion","title":"HSFM-$Σ$nn: Combining a Feedforward Motion Prediction Network and Covariance Prediction","date":"2020-09-09","arxiv_id":"2009.04299","n_code_links":0,"syntology":null},{"paper":null,"slug":"not-so-biggan-generating-high-fidelity-images","title":"not-so-BigGAN: Generating High-Fidelity Images on Small Compute with Wavelet-based Super-Resolution","date":"2020-09-09","arxiv_id":"2009.04433","n_code_links":0,"syntology":null},{"paper":null,"slug":"mipgan-generating-robust-and-high","title":"MIPGAN -- Generating Strong and High Quality Morphing Attacks Using Identity Prior Driven GAN","date":"2020-09-03","arxiv_id":"2009.01729","n_code_links":0,"syntology":null},{"paper":null,"slug":"multi-attention-network-for-semantic","title":"Multi-Attention-Network for Semantic Segmentation of Fine Resolution Remote Sensing Images","date":"2020-09-03","arxiv_id":"2009.02130","n_code_links":0,"syntology":null},{"paper":"/paper/text-and-style-conditioned-gan-for-generation","slug":"text-and-style-conditioned-gan-for-generation","title":"Text and Style Conditioned GAN for Generation of Offline Handwriting Lines","date":"2020-09-01","arxiv_id":"2009.00678","n_code_links":1,"syntology":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":null,"slug":"detecting-generic-music-features-with-single","title":"Detecting Generic Music Features with Single Layer Feedforward Network using Unsupervised Hebbian Computation","date":"2020-08-31","arxiv_id":"2008.13609","n_code_links":0,"syntology":null},{"paper":"/paper/soccogcom-at-semeval-2020-task-11","slug":"soccogcom-at-semeval-2020-task-11","title":"SocCogCom at SemEval-2020 Task 11: Characterizing and Detecting Propaganda using Sentence-Level Emotional Salience Features","date":"2020-08-29","arxiv_id":"2008.13012","n_code_links":1,"syntology":null},{"paper":"/paper/deeplandscape-adversarial-modeling-of","slug":"deeplandscape-adversarial-modeling-of","title":"DeepLandscape: Adversarial Modeling of Landscape Video","date":"2020-08-21","arxiv_id":"2008.09655","n_code_links":1,"syntology":null},{"paper":null,"slug":"reinforced-wasserstein-training-for-severity","title":"Reinforced Wasserstein Training for Severity-Aware Semantic Segmentation in Autonomous Driving","date":"2020-08-11","arxiv_id":"2008.04751","n_code_links":0,"syntology":null},{"paper":"/paper/spatiotemporal-contrastive-video","slug":"spatiotemporal-contrastive-video","title":"Spatiotemporal Contrastive Video Representation Learning","date":"2020-08-09","arxiv_id":"2008.03800","n_code_links":4,"syntology":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/styleflow-attribute-conditioned-exploration","slug":"styleflow-attribute-conditioned-exploration","title":"StyleFlow: Attribute-conditioned Exploration of StyleGAN-Generated Images using Conditional Continuous Normalizing Flows","date":"2020-08-06","arxiv_id":"2008.02401","n_code_links":3,"syntology":{"ran":9,"of":14,"n_ran_checked":8,"n_instrument":1,"unverified":5,"pointer_only":2,"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) · 5 unverified","official":{"repos":["rameenabdal/styleflow"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"paper":null,"slug":"stabilizing-deep-tomographic-reconstruction","title":"Stabilizing Deep Tomographic Reconstruction","date":"2020-08-04","arxiv_id":"2008.01846","n_code_links":0,"syntology":null},{"paper":"/paper/a-spectral-energy-distance-for-parallel","slug":"a-spectral-energy-distance-for-parallel","title":"A Spectral Energy Distance for Parallel Speech Synthesis","date":"2020-08-03","arxiv_id":"2008.01160","n_code_links":2,"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":{"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/delight-very-deep-and-light-weight","slug":"delight-very-deep-and-light-weight","title":"DeLighT: Deep and Light-weight Transformer","date":"2020-08-03","arxiv_id":"2008.00623","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: 0 honoured, 0 violated, 3 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","official":{"repos":["sacmehta/delight"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":0,"ran_from_kinds":["official"]}}},{"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/deeplandscape-adversarial-modeling-of-1","slug":"deeplandscape-adversarial-modeling-of-1","title":"DeepLandscape: Adversarial Modeling of Landscape Videos","date":"2020-08-01","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":"/paper/instance-selection-for-gans","slug":"instance-selection-for-gans","title":"Instance Selection for GANs","date":"2020-07-30","arxiv_id":"2007.15255","n_code_links":2,"syntology":{"ran":11,"of":19,"n_ran_checked":5,"n_instrument":6,"unverified":8,"pointer_only":19,"phrase":"11 ran (of which 0 constructed an object rather than computing a result; 5 with no instrument failure: 5 honoured, 0 violated, 0 with no contract checked; 6 where Syntology's instrument failed) · 8 unverified","official":{"repos":["uoguelph-mlrg/instance_selection_for_gans"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":3,"ran_from_kinds":["listed","official"]}}},{"paper":null,"slug":"on-the-transcriptomic-signature-and-general","title":"On the Transcriptomic Signature and General Stress State Associated with Aneuploidy","date":"2020-07-28","arxiv_id":"2007.14585","n_code_links":0,"syntology":null},{"paper":"/paper/macu-net-semantic-segmentation-from-high","slug":"macu-net-semantic-segmentation-from-high","title":"MACU-Net for Semantic Segmentation of Fine-Resolution Remotely Sensed Images","date":"2020-07-26","arxiv_id":"2007.13083","n_code_links":2,"syntology":null},{"paper":null,"slug":"interpolating-gans-to-scaffold-autotelic","title":"Interpolating GANs to Scaffold Autotelic Creativity","date":"2020-07-21","arxiv_id":"2007.11119","n_code_links":0,"syntology":null},{"paper":null,"slug":"detection-attribution-and-localization-of-gan","title":"Detection, Attribution and Localization of GAN Generated Images","date":"2020-07-20","arxiv_id":"2007.10466","n_code_links":0,"syntology":null},{"paper":"/paper/generative-hierarchical-features-from","slug":"generative-hierarchical-features-from","title":"Generative Hierarchical Features from Synthesizing Images","date":"2020-07-20","arxiv_id":"2007.10379","n_code_links":1,"syntology":null},{"paper":"/paper/developmental-reinforcement-learning-of","slug":"developmental-reinforcement-learning-of","title":"Developmental Reinforcement Learning of Control Policy of a Quadcopter UAV with Thrust Vectoring Rotors","date":"2020-07-15","arxiv_id":"2007.07793","n_code_links":1,"syntology":null},{"paper":null,"slug":"allpass-feedback-delay-networks","title":"Allpass Feedback Delay Networks","date":"2020-07-14","arxiv_id":"2007.07337","n_code_links":0,"syntology":null},{"paper":"/paper/biological-credit-assignment-through-dynamic","slug":"biological-credit-assignment-through-dynamic","title":"Biological credit assignment through dynamic inversion of feedforward networks","date":"2020-07-10","arxiv_id":"2007.05112","n_code_links":0,"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":null}},{"paper":"/paper/a-free-viewpoint-portrait-generator-with","slug":"a-free-viewpoint-portrait-generator-with","title":"SofGAN: A Portrait Image Generator with Dynamic Styling","date":"2020-07-07","arxiv_id":"2007.03780","n_code_links":1,"syntology":null},{"paper":null,"slug":"can-gan-generated-morphs-threaten-face","title":"Can GAN Generated Morphs Threaten Face Recognition Systems Equally as Landmark Based Morphs? -- Vulnerability and Detection","date":"2020-07-07","arxiv_id":"2007.03621","n_code_links":0,"syntology":null},{"paper":"/paper/weak-sindy-for-partial-differential-equations","slug":"weak-sindy-for-partial-differential-equations","title":"Weak SINDy For Partial Differential Equations","date":"2020-07-06","arxiv_id":"2007.02848","n_code_links":2,"syntology":null},{"paper":null,"slug":"collaborative-learning-for-faster-stylegan","title":"Collaborative Learning for Faster StyleGAN Embedding","date":"2020-07-03","arxiv_id":"2007.01758","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-simple-and-effective-dependency-parser-for","title":"A Simple and Effective Dependency Parser for Telugu","date":"2020-07-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":"/paper/enhancing-least-square-channel-estimation","slug":"enhancing-least-square-channel-estimation","title":"Enhancing Least Square Channel Estimation Using Deep Learning","date":"2020-06-30","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":"/paper/priorgan-real-data-prior-for-generative","slug":"priorgan-real-data-prior-for-generative","title":"PriorGAN: Real Data Prior for Generative Adversarial Nets","date":"2020-06-30","arxiv_id":"2006.16990","n_code_links":1,"syntology":null},{"paper":"/paper/parametric-instance-classification-for","slug":"parametric-instance-classification-for","title":"Parametric Instance Classification for Unsupervised Visual Feature Learning","date":"2020-06-25","arxiv_id":"2006.14618","n_code_links":1,"syntology":null},{"paper":"/paper/hyperparameter-ensembles-for-robustness-and","slug":"hyperparameter-ensembles-for-robustness-and","title":"Hyperparameter Ensembles for Robustness and Uncertainty Quantification","date":"2020-06-24","arxiv_id":"2006.13570","n_code_links":3,"syntology":{"ran":2,"of":4,"n_ran_checked":1,"n_instrument":1,"unverified":2,"pointer_only":0,"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) · 2 unverified","official":{"repos":["google/uncertainty-baselines"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":1,"n_ran_no_instrument_failure":1,"n_unverified":2,"ran_from_kinds":["official"]}}},{"paper":"/paper/deep-learning-based-channel-estimation-2","slug":"deep-learning-based-channel-estimation-2","title":"Deep Learning Based Channel Estimation Schemes for IEEE 802.11p Standard","date":"2020-06-18","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":"/paper/differentiable-augmentation-for-data","slug":"differentiable-augmentation-for-data","title":"Differentiable Augmentation for Data-Efficient GAN Training","date":"2020-06-18","arxiv_id":"2006.10738","n_code_links":13,"syntology":{"ran":49,"of":58,"n_ran_checked":19,"n_instrument":30,"unverified":9,"pointer_only":15,"phrase":"49 ran (of which 0 constructed an object rather than computing a result; 19 with no instrument failure: 2 honoured, 1 violated, 16 with no contract checked; 30 where Syntology's instrument failed) · 9 unverified","official":{"repos":["mit-han-lab/data-efficient-gans"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed","official"]}}},{"paper":"/paper/dynamic-tensor-rematerialization","slug":"dynamic-tensor-rematerialization","title":"Dynamic Tensor Rematerialization","date":"2020-06-17","arxiv_id":"2006.09616","n_code_links":1,"syntology":null},{"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":null,"slug":"generating-master-faces-for-use-in-performing","title":"Generating Master Faces for Use in Performing Wolf Attacks on Face Recognition Systems","date":"2020-06-15","arxiv_id":"2006.08376","n_code_links":0,"syntology":null},{"paper":null,"slug":"online-sequential-extreme-learning-machines","title":"Online Sequential Extreme Learning Machines: Features Combined From Hundreds of Midlayers","date":"2020-06-12","arxiv_id":"2006.06893","n_code_links":0,"syntology":null},{"paper":"/paper/training-generative-adversarial-networks-with-2","slug":"training-generative-adversarial-networks-with-2","title":"Training Generative Adversarial Networks with Limited Data","date":"2020-06-11","arxiv_id":"2006.06676","n_code_links":28,"syntology":{"ran":21,"of":29,"n_ran_checked":20,"n_instrument":1,"unverified":8,"pointer_only":5,"phrase":"21 ran (of which 0 constructed an object rather than computing a result; 20 with no instrument failure: 2 honoured, 1 violated, 17 with no contract checked; 1 where Syntology's instrument failed) · 8 unverified","official":{"repos":["NVlabs/stylegan2-ada"],"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/big-gans-are-watching-you-towards","slug":"big-gans-are-watching-you-towards","title":"Object Segmentation Without Labels with Large-Scale Generative Models","date":"2020-06-08","arxiv_id":"2006.04988","n_code_links":1,"syntology":null},{"paper":null,"slug":"learning-disconnected-manifolds-a-no-gans","title":"Learning disconnected manifolds: a no GANs land","date":"2020-06-08","arxiv_id":"2006.04596","n_code_links":0,"syntology":null},{"paper":"/paper/ciwgan-and-fiwgan-encoding-information-in","slug":"ciwgan-and-fiwgan-encoding-information-in","title":"CiwGAN and fiwGAN: Encoding information in acoustic data to model lexical learning with Generative Adversarial Networks","date":"2020-06-04","arxiv_id":"2006.02951","n_code_links":1,"syntology":null},{"paper":null,"slug":"neural-network-for-low-memory-iot-devices-and","title":"Neural Network for Low-Memory IoT Devices and MNIST Image Recognition Using Kernels Based on Logistic Map","date":"2020-06-04","arxiv_id":"2006.02824","n_code_links":0,"syntology":null},{"paper":null,"slug":"renyi-generative-adversarial-networks","title":"Least $k$th-Order and Rényi Generative Adversarial Networks","date":"2020-06-03","arxiv_id":"2006.02479","n_code_links":0,"syntology":null},{"paper":"/paper/a-u-net-based-discriminator-for-generative-1","slug":"a-u-net-based-discriminator-for-generative-1","title":"A U-Net Based Discriminator for Generative Adversarial Networks","date":"2020-06-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":"/paper/rnns-on-monitoring-physical-activity-energy","slug":"rnns-on-monitoring-physical-activity-energy","title":"RNNs on Monitoring Physical Activity Energy Expenditure in Older People","date":"2020-06-01","arxiv_id":"2006.01169","n_code_links":1,"syntology":null},{"paper":null,"slug":"severity-aware-semantic-segmentation-with","title":"Severity-Aware Semantic Segmentation With Reinforced Wasserstein Training","date":"2020-06-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"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/network-fusion-for-content-creation-with","slug":"network-fusion-for-content-creation-with","title":"Network-to-Network Translation with Conditional Invertible Neural Networks","date":"2020-05-27","arxiv_id":"2005.13580","n_code_links":1,"syntology":null},{"paper":"/paper/safeml-safety-monitoring-of-machine-learning","slug":"safeml-safety-monitoring-of-machine-learning","title":"SafeML: Safety Monitoring of Machine Learning Classifiers through Statistical Difference Measure","date":"2020-05-27","arxiv_id":"2005.13166","n_code_links":2,"syntology":null},{"paper":null,"slug":"sparse-identification-of-nonlinear-dynamical","title":"Sparse Identification of Nonlinear Dynamical Systems via Reweighted $\\ell_1$-regularized Least Squares","date":"2020-05-27","arxiv_id":"2005.13232","n_code_links":0,"syntology":null},{"paper":"/paper/end-to-end-object-detection-with-transformers","slug":"end-to-end-object-detection-with-transformers","title":"End-to-End Object Detection with Transformers","date":"2020-05-26","arxiv_id":"2005.12872","n_code_links":37,"syntology":{"ran":70,"of":92,"n_ran_checked":62,"n_instrument":8,"unverified":22,"pointer_only":19,"phrase":"70 ran (of which 45 constructed an object rather than computing a result; 62 with no instrument failure: 2 honoured, 1 violated, 59 with no contract checked; 8 where Syntology's instrument failed) · 22 unverified","official":{"repos":["facebookresearch/detr"],"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/learning-to-classify-images-without-labels","slug":"learning-to-classify-images-without-labels","title":"SCAN: Learning to Classify Images without Labels","date":"2020-05-25","arxiv_id":"2005.12320","n_code_links":2,"syntology":null}],"record_sha256":"1b4e36c02637e1f168ef057a6d76399bb26bbe7b51059309f09608bc8c22b35a","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}