{"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/test/papers/61","list_of":"/method/test","method":"Test","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":61,"pages_in_order":65,"rows_per_page":100,"rows":[6001,6100],"of":6434,"counts":{"archive_papers_tagged":6434,"with_a_code_link":2339,"where_syntology_ran_a_sample":517,"not_listed_spam_title":0,"listed":6434,"listed_where_code_ran":517,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":428,"every_run_a_failure_of_syntologys_instrument":89,"listed_with_a_run_with_no_instrument_failure":428,"listed_every_run_a_failure_of_syntologys_instrument":89,"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/test","prev":"/method/test/papers/60","next":"/method/test/papers/62","papers":[{"paper":"/paper/istego100k-large-scale-image-steganalysis","slug":"istego100k-large-scale-image-steganalysis","title":"IStego100K: Large-scale Image Steganalysis Dataset","date":"2019-11-13","arxiv_id":"1911.05542","n_code_links":1,"syntology":null},{"paper":null,"slug":"reinforcement-learning-driven-test-generation","title":"Reinforcement Learning-Driven Test Generation for Android GUI Applications using Formal Specifications","date":"2019-11-13","arxiv_id":"1911.05403","n_code_links":0,"syntology":null},{"paper":"/paper/selective-brain-damage-measuring-the","slug":"selective-brain-damage-measuring-the","title":"What Do Compressed Deep Neural Networks Forget?","date":"2019-11-13","arxiv_id":"1911.05248","n_code_links":2,"syntology":null},{"paper":null,"slug":"structured-sparsification-of-gated-recurrent","title":"Structured Sparsification of Gated Recurrent Neural Networks","date":"2019-11-13","arxiv_id":"1911.05585","n_code_links":0,"syntology":null},{"paper":"/paper/a-probabilistic-approach-for-predicting","slug":"a-probabilistic-approach-for-predicting","title":"Predicting Landslides Using Contour Aligning Convolutional Neural Networks","date":"2019-11-12","arxiv_id":"1911.04651","n_code_links":3,"syntology":null},{"paper":"/paper/a-syntax-aware-multi-task-learning-framework-1","slug":"a-syntax-aware-multi-task-learning-framework-1","title":"A Syntax-aware Multi-task Learning Framework for Chinese Semantic Role Labeling","date":"2019-11-12","arxiv_id":"1911.04641","n_code_links":1,"syntology":null},{"paper":null,"slug":"data-free-point-cloud-network-for-3d-face","title":"Data-Free Point Cloud Network for 3D Face Recognition","date":"2019-11-12","arxiv_id":"1911.04731","n_code_links":0,"syntology":null},{"paper":null,"slug":"deep-clustering-for-mars-rover-image-datasets","title":"Deep Clustering for Mars Rover image datasets","date":"2019-11-12","arxiv_id":"1911.06623","n_code_links":0,"syntology":null},{"paper":null,"slug":"deep-generative-models-strike-back-improving","title":"Deep Generative Models Strike Back! Improving Understanding and Evaluation in Light of Unmet Expectations for OoD Data","date":"2019-11-12","arxiv_id":"1911.04699","n_code_links":0,"syntology":null},{"paper":null,"slug":"deep-variational-semi-supervised-novelty-1","title":"Deep Variational Semi-Supervised Novelty Detection","date":"2019-11-12","arxiv_id":"1911.04971","n_code_links":0,"syntology":null},{"paper":null,"slug":"improving-robustness-of-task-oriented-dialog","title":"Improving Robustness of Task Oriented Dialog Systems","date":"2019-11-12","arxiv_id":"1911.05153","n_code_links":0,"syntology":null},{"paper":null,"slug":"investigating-constraint-programming-and","title":"Investigating Constraint Programming and Hybrid Methods for Real World Industrial Test Laboratory Scheduling","date":"2019-11-12","arxiv_id":"1911.04766","n_code_links":0,"syntology":null},{"paper":null,"slug":"novel-multi-objectivization-approaches-for","title":"Multi-objectivization Inspired Metaheuristics for the Sum-of-the-Parts Combinatorial Optimization Problems","date":"2019-11-12","arxiv_id":"1911.04658","n_code_links":0,"syntology":null},{"paper":"/paper/on-robustness-to-adversarial-examples-and-1","slug":"on-robustness-to-adversarial-examples-and-1","title":"On Robustness to Adversarial Examples and Polynomial Optimization","date":"2019-11-12","arxiv_id":"1911.04681","n_code_links":1,"syntology":null},{"paper":null,"slug":"semi-supervised-multi-organ-segmentation","title":"Semi-Supervised Multi-Organ Segmentation through Quality Assurance Supervision","date":"2019-11-12","arxiv_id":"1911.05113","n_code_links":0,"syntology":null},{"paper":"/paper/unsupervised-medical-image-segmentation-with","slug":"unsupervised-medical-image-segmentation-with","title":"Unsupervised Medical Image Segmentation with Adversarial Networks: From Edge Diagrams to Segmentation Maps","date":"2019-11-12","arxiv_id":"1911.05140","n_code_links":1,"syntology":null},{"paper":null,"slug":"diversity-by-phonetics-and-its-application-in","title":"Diversity by Phonetics and its Application in Neural Machine Translation","date":"2019-11-11","arxiv_id":"1911.04292","n_code_links":0,"syntology":null},{"paper":null,"slug":"making-good-on-lstms-unfulfilled-promise","title":"Making Good on LSTMs' Unfulfilled Promise","date":"2019-11-11","arxiv_id":"1911.04489","n_code_links":0,"syntology":null},{"paper":"/paper/privacy-preserving-multiple-tensor","slug":"privacy-preserving-multiple-tensor","title":"Privacy-Preserving Multiple Tensor Factorization for Synthesizing Large-Scale Location Traces with Cluster-Specific Features","date":"2019-11-11","arxiv_id":"1911.04226","n_code_links":1,"syntology":null},{"paper":"/paper/self-training-with-noisy-student-improves","slug":"self-training-with-noisy-student-improves","title":"Self-training with Noisy Student improves ImageNet classification","date":"2019-11-11","arxiv_id":"1911.04252","n_code_links":13,"syntology":{"ran":13,"of":24,"n_ran_checked":10,"n_instrument":3,"unverified":11,"pointer_only":2,"phrase":"13 ran (of which 0 constructed an object rather than computing a result; 10 with no instrument failure: 2 honoured, 0 violated, 8 with no contract checked; 3 where Syntology's instrument failed) · 11 unverified","official":{"repos":["google-research/noisystudent","tensorflow/tpu"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":10,"ran_from_kinds":["listed","official"]}}},{"paper":null,"slug":"systematic-comparison-of-the-influence-of","title":"Systematic Comparison of the Influence of Different Data Preprocessing Methods on the Performance of Gait Classifications Using Machine Learning","date":"2019-11-11","arxiv_id":"1911.04335","n_code_links":0,"syntology":null},{"paper":null,"slug":"tool-substitution-with-shape-and-material","title":"Tool Substitution with Shape and Material Reasoning Using Dual Neural Networks","date":"2019-11-11","arxiv_id":"1911.04521","n_code_links":0,"syntology":null},{"paper":null,"slug":"understanding-bert-performance-in-propaganda-1","title":"Understanding BERT performance in propaganda analysis","date":"2019-11-11","arxiv_id":"1911.04525","n_code_links":0,"syntology":null},{"paper":"/paper/a-bilingual-generative-transformer-for-1","slug":"a-bilingual-generative-transformer-for-1","title":"A Bilingual Generative Transformer for Semantic Sentence Embedding","date":"2019-11-10","arxiv_id":"1911.03895","n_code_links":2,"syntology":null},{"paper":"/paper/ccmatrix-mining-billions-of-high-quality","slug":"ccmatrix-mining-billions-of-high-quality","title":"CCMatrix: Mining Billions of High-Quality Parallel Sentences on the WEB","date":"2019-11-10","arxiv_id":"1911.04944","n_code_links":3,"syntology":null},{"paper":"/paper/generalizing-natural-language-analysis-1","slug":"generalizing-natural-language-analysis-1","title":"Generalizing Natural Language Analysis through Span-relation Representations","date":"2019-11-10","arxiv_id":"1911.03822","n_code_links":3,"syntology":null},{"paper":null,"slug":"location-attention-for-extrapolation-to","title":"Location Attention for Extrapolation to Longer Sequences","date":"2019-11-10","arxiv_id":"1911.03872","n_code_links":0,"syntology":null},{"paper":"/paper/rethinking-self-attention-an-interpretable","slug":"rethinking-self-attention-an-interpretable","title":"Rethinking Self-Attention: Towards Interpretability in Neural Parsing","date":"2019-11-10","arxiv_id":"1911.03875","n_code_links":2,"syntology":{"ran":1,"of":3,"n_ran_checked":0,"n_instrument":1,"unverified":2,"pointer_only":3,"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":["KhalilMrini/LAL-Parser"],"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":null,"slug":"translationese-as-a-language-in-multilingual","title":"Translationese as a Language in \"Multilingual\" NMT","date":"2019-11-10","arxiv_id":"1911.03823","n_code_links":0,"syntology":null},{"paper":"/paper/accurate-protein-structure-prediction-by","slug":"accurate-protein-structure-prediction-by","title":"Accurate Protein Structure Prediction by Embeddings and Deep Learning Representations","date":"2019-11-09","arxiv_id":"1911.05531","n_code_links":3,"syntology":null},{"paper":null,"slug":"action-recognition-using-supervised-spiking","title":"Action Recognition Using Supervised Spiking Neural Networks","date":"2019-11-09","arxiv_id":"1911.03630","n_code_links":0,"syntology":null},{"paper":"/paper/commongen-a-constrained-text-generation","slug":"commongen-a-constrained-text-generation","title":"CommonGen: A Constrained Text Generation Challenge for Generative Commonsense Reasoning","date":"2019-11-09","arxiv_id":"1911.03705","n_code_links":3,"syntology":{"ran":5,"of":6,"n_ran_checked":5,"n_instrument":0,"unverified":1,"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) · 1 unverified","official":null}},{"paper":"/paper/factored-latent-dynamic-conditional-random","slug":"factored-latent-dynamic-conditional-random","title":"Factored Latent-Dynamic Conditional Random Fields for Single and Multi-label Sequence Modeling","date":"2019-11-09","arxiv_id":"1911.03667","n_code_links":1,"syntology":null},{"paper":"/paper/hate-speech-detection-on-vietnamese-social","slug":"hate-speech-detection-on-vietnamese-social","title":"Hate Speech Detection on Vietnamese Social Media Text using the Bidirectional-LSTM Model","date":"2019-11-09","arxiv_id":"1911.03648","n_code_links":1,"syntology":null},{"paper":null,"slug":"l-fgadmm-layer-wise-federated-group-admm-for","title":"L-FGADMM: Layer-Wise Federated Group ADMM for Communication Efficient Decentralized Deep Learning","date":"2019-11-09","arxiv_id":"1911.03654","n_code_links":0,"syntology":null},{"paper":"/paper/learning-to-optimize-in-swarms","slug":"learning-to-optimize-in-swarms","title":"Learning to Optimize in Swarms","date":"2019-11-09","arxiv_id":"1911.03787","n_code_links":1,"syntology":null},{"paper":"/paper/on-the-design-of-convolutional-neural","slug":"on-the-design-of-convolutional-neural","title":"On the design of convolutional neural networks for automatic detection of Alzheimer's disease","date":"2019-11-09","arxiv_id":"1911.03740","n_code_links":1,"syntology":null},{"paper":"/paper/spatially-regularized-parametric-map","slug":"spatially-regularized-parametric-map","title":"Spatially Regularized Parametric Map Reconstruction for Fast Magnetic Resonance Fingerprinting","date":"2019-11-09","arxiv_id":"1911.03786","n_code_links":1,"syntology":null},{"paper":null,"slug":"table-to-text-natural-language-generation","title":"Table-to-Text Natural Language Generation with Unseen Schemas","date":"2019-11-09","arxiv_id":"1911.03601","n_code_links":0,"syntology":null},{"paper":"/paper/towards-understanding-gender-bias-in-relation","slug":"towards-understanding-gender-bias-in-relation","title":"Towards Understanding Gender Bias in Relation Extraction","date":"2019-11-09","arxiv_id":"1911.03642","n_code_links":1,"syntology":{"ran":2,"of":5,"n_ran_checked":1,"n_instrument":1,"unverified":3,"pointer_only":5,"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) · 3 unverified","official":null}},{"paper":"/paper/a-binary-regression-adaptive-goodness-of-fit","slug":"a-binary-regression-adaptive-goodness-of-fit","title":"Is a Classification Procedure Good Enough? A Goodness-of-Fit Assessment Tool for Classification Learning","date":"2019-11-08","arxiv_id":"1911.03063","n_code_links":1,"syntology":null},{"paper":"/paper/a-good-sample-is-hard-to-find-noise-injection","slug":"a-good-sample-is-hard-to-find-noise-injection","title":"A Good Sample is Hard to Find: Noise Injection Sampling and Self-Training for Neural Language Generation Models","date":"2019-11-08","arxiv_id":"1911.03373","n_code_links":1,"syntology":null},{"paper":"/paper/a-multiple-testing-framework-for-diagnostic","slug":"a-multiple-testing-framework-for-diagnostic","title":"A multiple testing framework for diagnostic accuracy studies with co-primary endpoints","date":"2019-11-08","arxiv_id":"1911.02982","n_code_links":1,"syntology":null},{"paper":null,"slug":"advances-in-machine-learning-for-the","title":"Advances in Machine Learning for the Behavioral Sciences","date":"2019-11-08","arxiv_id":"1911.03249","n_code_links":0,"syntology":null},{"paper":null,"slug":"autoids-auto-encoder-based-method-for","title":"AutoIDS: Auto-encoder Based Method for Intrusion Detection System","date":"2019-11-08","arxiv_id":"1911.03306","n_code_links":0,"syntology":null},{"paper":null,"slug":"cross-lingual-relevance-transfer-for-document","title":"Cross-Lingual Relevance Transfer for Document Retrieval","date":"2019-11-08","arxiv_id":"1911.02989","n_code_links":0,"syntology":null},{"paper":"/paper/domain-robustness-in-neural-machine","slug":"domain-robustness-in-neural-machine","title":"Domain Robustness in Neural Machine Translation","date":"2019-11-08","arxiv_id":"1911.03109","n_code_links":2,"syntology":{"ran":10,"of":11,"n_ran_checked":10,"n_instrument":0,"unverified":1,"pointer_only":0,"phrase":"10 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; 0 where Syntology's instrument failed) · 1 unverified","official":{"repos":["ZurichNLP/domain-robustness","ZurichNLP/sockeye"],"state":"official (archive's flag): 10 ran","n_ran":10,"n_constructed":0,"n_ran_no_instrument_failure":10,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":"/paper/interactive-refinement-of-cross-lingual-word","slug":"interactive-refinement-of-cross-lingual-word","title":"Interactive Refinement of Cross-Lingual Word Embeddings","date":"2019-11-08","arxiv_id":"1911.03070","n_code_links":1,"syntology":{"ran":11,"of":17,"n_ran_checked":11,"n_instrument":0,"unverified":6,"pointer_only":0,"phrase":"11 ran (of which 0 constructed an object rather than computing a result; 11 with no instrument failure: 1 honoured, 0 violated, 10 with no contract checked; 0 where Syntology's instrument failed) · 6 unverified","official":{"repos":["forest-snow/clime-ui"],"state":"official (archive's flag): 11 ran","n_ran":11,"n_constructed":0,"n_ran_no_instrument_failure":11,"n_unverified":6,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"learning-accelerated-admm-for-distributed","title":"Learning-Accelerated ADMM for Distributed Optimal Power Flow","date":"2019-11-08","arxiv_id":"1911.03019","n_code_links":0,"syntology":null},{"paper":null,"slug":"non-parametric-probabilistic-load-flow-using","title":"Non-parametric Probabilistic Load Flow using Gaussian Process Learning","date":"2019-11-08","arxiv_id":"1911.03093","n_code_links":0,"syntology":null},{"paper":"/paper/recurrent-neural-network-transducer-for-audio","slug":"recurrent-neural-network-transducer-for-audio","title":"Recurrent Neural Network Transducer for Audio-Visual Speech Recognition","date":"2019-11-08","arxiv_id":"1911.04890","n_code_links":1,"syntology":null},{"paper":null,"slug":"two-stage-wecc-composite-load-modeling-a","title":"Two-stage WECC Composite Load Modeling: A Double Deep Q-Learning Networks Approach","date":"2019-11-08","arxiv_id":"1911.04894","n_code_links":0,"syntology":null},{"paper":null,"slug":"why-do-masked-neural-language-models-still","title":"Why Do Masked Neural Language Models Still Need Common Sense Knowledge?","date":"2019-11-08","arxiv_id":"1911.03024","n_code_links":0,"syntology":null},{"paper":null,"slug":"accounting-for-physics-uncertainty-in","title":"Accounting for Physics Uncertainty in Ultrasonic Wave Propagation using Deep Learning","date":"2019-11-07","arxiv_id":"1911.02743","n_code_links":0,"syntology":null},{"paper":null,"slug":"change-your-singer-a-transfer-learning","title":"Change your singer: a transfer learning generative adversarial framework for song to song conversion","date":"2019-11-07","arxiv_id":"1911.02933","n_code_links":0,"syntology":null},{"paper":"/paper/confidence-intervals-for-policy-evaluation-in","slug":"confidence-intervals-for-policy-evaluation-in","title":"Confidence Intervals for Policy Evaluation in Adaptive Experiments","date":"2019-11-07","arxiv_id":"1911.02768","n_code_links":1,"syntology":null},{"paper":"/paper/dice-loss-for-data-imbalanced-nlp-tasks","slug":"dice-loss-for-data-imbalanced-nlp-tasks","title":"Dice Loss for Data-imbalanced NLP Tasks","date":"2019-11-07","arxiv_id":"1911.02855","n_code_links":4,"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":["ShannonAI/dice_loss_for_NLP"],"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/h_inf-model-free-reinforcement-learning-with","slug":"h_inf-model-free-reinforcement-learning-with","title":"$H_\\infty$ Model-free Reinforcement Learning with Robust Stability Guarantee","date":"2019-11-07","arxiv_id":"1911.02875","n_code_links":1,"syntology":null},{"paper":null,"slug":"impact-of-narrow-lanes-on-arterial-road","title":"Impact of Narrow Lanes on Arterial Road Vehicle Crashes: A Machine Learning Approach","date":"2019-11-07","arxiv_id":"1911.04954","n_code_links":0,"syntology":null},{"paper":null,"slug":"sequence-aware-factorization-machines-for","title":"Sequence-Aware Factorization Machines for Temporal Predictive Analytics","date":"2019-11-07","arxiv_id":"1911.02752","n_code_links":0,"syntology":null},{"paper":null,"slug":"teacher-student-training-for-robust-tacotron","title":"Teacher-Student Training for Robust Tacotron-based TTS","date":"2019-11-07","arxiv_id":"1911.02839","n_code_links":0,"syntology":null},{"paper":null,"slug":"the-lig-system-for-the-english-czech-text","title":"The LIG system for the English-Czech Text Translation Task of IWSLT 2019","date":"2019-11-07","arxiv_id":"1911.02898","n_code_links":0,"syntology":null},{"paper":null,"slug":"vistra2-video-coding-using-spatial-resolution","title":"ViSTRA2: Video Coding using Spatial Resolution and Effective Bit Depth Adaptation","date":"2019-11-07","arxiv_id":"1911.02833","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-spoken-dialogue-system-for-spatial-question","title":"A Spoken Dialogue System for Spatial Question Answering in a Physical Blocks World","date":"2019-11-06","arxiv_id":"1911.02524","n_code_links":0,"syntology":null},{"paper":null,"slug":"domain-translationese-and-noise-in-synthetic","title":"Domain, Translationese and Noise in Synthetic Data for Neural Machine Translation","date":"2019-11-06","arxiv_id":"1911.03362","n_code_links":0,"syntology":null},{"paper":null,"slug":"high-dimensional-black-box-optimization-under","title":"High-dimensional Black-box Optimization Under Uncertainty","date":"2019-11-06","arxiv_id":"1911.02457","n_code_links":0,"syntology":null},{"paper":null,"slug":"invariance-and-identifiability-issues-for","title":"Invariance and identifiability issues for word embeddings","date":"2019-11-06","arxiv_id":"1911.02656","n_code_links":0,"syntology":null},{"paper":null,"slug":"machine-learning-using-the-variational","title":"Machine Learning using the Variational Predictive Information Bottleneck with a Validation Set","date":"2019-11-06","arxiv_id":"1911.02210","n_code_links":0,"syntology":null},{"paper":null,"slug":"minimax-nonparametric-parallelism-test","title":"Minimax Nonparametric Two-sample Test under Smoothing","date":"2019-11-06","arxiv_id":"1911.02171","n_code_links":0,"syntology":null},{"paper":null,"slug":"randomized-computer-vision-approaches-for","title":"Randomized Computer Vision Approaches for Pattern Recognition in Timepix and Timepix3 Detectors","date":"2019-11-06","arxiv_id":"1911.02367","n_code_links":0,"syntology":null},{"paper":null,"slug":"resilient-load-restoration-in-microgrids","title":"Resilient Load Restoration in Microgrids Considering Mobile Energy Storage Fleets: A Deep Reinforcement Learning Approach","date":"2019-11-06","arxiv_id":"1911.02206","n_code_links":0,"syntology":null},{"paper":"/paper/shaping-visual-representations-with-language","slug":"shaping-visual-representations-with-language","title":"Shaping Visual Representations with Language for Few-shot Classification","date":"2019-11-06","arxiv_id":"1911.02683","n_code_links":2,"syntology":null},{"paper":"/paper/unsupervised-multi-document-opinion","slug":"unsupervised-multi-document-opinion","title":"Unsupervised Opinion Summarization as Copycat-Review Generation","date":"2019-11-06","arxiv_id":"1911.02247","n_code_links":3,"syntology":null},{"paper":null,"slug":"user-intended-doppler-measurement-type","title":"Doppler Spectrum Classification with CNNs via Heatmap Location Encoding and a Multi-head Output Layer","date":"2019-11-06","arxiv_id":"1911.02407","n_code_links":0,"syntology":null},{"paper":null,"slug":"efficiently-learning-structured-distributions","title":"Efficiently Learning Structured Distributions from Untrusted Batches","date":"2019-11-05","arxiv_id":"1911.02035","n_code_links":0,"syntology":null},{"paper":"/paper/small-footprint-keyword-spotting-on-raw-audio","slug":"small-footprint-keyword-spotting-on-raw-audio","title":"Small-Footprint Keyword Spotting on Raw Audio Data with Sinc-Convolutions","date":"2019-11-05","arxiv_id":"1911.02086","n_code_links":1,"syntology":null},{"paper":"/paper/test-metrics-for-recurrent-neural-networks","slug":"test-metrics-for-recurrent-neural-networks","title":"Coverage Guided Testing for Recurrent Neural Networks","date":"2019-11-05","arxiv_id":"1911.01952","n_code_links":1,"syntology":null},{"paper":null,"slug":"training-neural-machine-translation-nmt","title":"Training Neural Machine Translation (NMT) Models using Tensor Train Decomposition on TensorFlow (T3F)","date":"2019-11-05","arxiv_id":"1911.01933","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-novel-approach-to-enhance-the-performance","title":"A Novel Approach to Enhance the Performance of Semantic Search in Bengali using Neural Net and other Classification Techniques","date":"2019-11-04","arxiv_id":"1911.01256","n_code_links":0,"syntology":null},{"paper":"/paper/automated-estimation-of-the-spinal-curvature","slug":"automated-estimation-of-the-spinal-curvature","title":"Automated Estimation of the Spinal Curvature via Spine Centerline Extraction with Ensembles of Cascaded Neural Networks","date":"2019-11-04","arxiv_id":"1911.01126","n_code_links":1,"syntology":null},{"paper":null,"slug":"evolution-based-fine-tuning-of-cnns-for","title":"Evolution-based Fine-tuning of CNNs for Prostate Cancer Detection","date":"2019-11-04","arxiv_id":"1911.01477","n_code_links":0,"syntology":null},{"paper":null,"slug":"field-of-view-extension-in-computed","title":"Field of View Extension in Computed Tomography Using Deep Learning Prior","date":"2019-11-04","arxiv_id":"1911.01178","n_code_links":0,"syntology":null},{"paper":null,"slug":"optimal-transport-based-change-point","title":"Optimal Transport Based Change Point Detection and Time Series Segment Clustering","date":"2019-11-04","arxiv_id":"1911.01325","n_code_links":0,"syntology":null},{"paper":null,"slug":"predicting-the-properties-of-black-holes","title":"Predicting the properties of black holes merger remnants with Deep Neural Networks","date":"2019-11-04","arxiv_id":"1911.01496","n_code_links":0,"syntology":null},{"paper":null,"slug":"probabilistic-super-resolution-of-solar","title":"Probabilistic Super-Resolution of Solar Magnetograms: Generating Many Explanations and Measuring Uncertainties","date":"2019-11-04","arxiv_id":"1911.01486","n_code_links":0,"syntology":null},{"paper":"/paper/self-supervised-difference-detection-for-1","slug":"self-supervised-difference-detection-for-1","title":"Self-Supervised Difference Detection for Weakly-Supervised Semantic Segmentation","date":"2019-11-04","arxiv_id":"1911.01370","n_code_links":1,"syntology":{"ran":6,"of":8,"n_ran_checked":6,"n_instrument":0,"unverified":2,"pointer_only":1,"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) · 2 unverified","official":{"repos":["shimoda-uec/ssdd"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":2,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"singular-points-detection-with-semantic","title":"Singular points detection with semantic segmentation networks","date":"2019-11-04","arxiv_id":"1911.01106","n_code_links":0,"syntology":null},{"paper":"/paper/adversarial-target-invariant-representation","slug":"adversarial-target-invariant-representation","title":"Generalizing to unseen domains via distribution matching","date":"2019-11-03","arxiv_id":"1911.00804","n_code_links":2,"syntology":{"ran":0,"of":1,"n_ran_checked":0,"n_instrument":0,"unverified":1,"pointer_only":0,"phrase":"0 ran · 1 unverified","official":null}},{"paper":null,"slug":"computationally-efficient-versions-of","title":"Computationally efficient versions of conformal predictive distributions","date":"2019-11-03","arxiv_id":"1911.00941","n_code_links":0,"syntology":null},{"paper":null,"slug":"gland-segmentation-in-histopathological","title":"Gland Segmentation in Histopathological Images by Deep Neural Network","date":"2019-11-03","arxiv_id":"1911.00909","n_code_links":0,"syntology":null},{"paper":null,"slug":"imitation-in-the-imitation-game","title":"Imitation in the Imitation Game","date":"2019-11-03","arxiv_id":"1911.06893","n_code_links":0,"syntology":null},{"paper":null,"slug":"privacy-for-free-communication-efficient","title":"Privacy for Free: Communication-Efficient Learning with Differential Privacy Using Sketches","date":"2019-11-03","arxiv_id":"1911.00972","n_code_links":0,"syntology":null},{"paper":null,"slug":"sentiment-analysis-model-for-twitter-data-in","title":"Sentiment analysis model for Twitter data in Polish language","date":"2019-11-03","arxiv_id":"1911.00985","n_code_links":0,"syntology":null},{"paper":null,"slug":"automated-inline-analysis-of-myocardial","title":"Automated Inline Analysis of Myocardial Perfusion MRI with Deep Learning","date":"2019-11-02","arxiv_id":"1911.00625","n_code_links":0,"syntology":null},{"paper":null,"slug":"design-and-challenges-of-cloze-style-reading","title":"Design and Challenges of Cloze-Style Reading Comprehension Tasks on Multiparty Dialogue","date":"2019-11-02","arxiv_id":"1911.00773","n_code_links":0,"syntology":null},{"paper":null,"slug":"fair-predictors-under-distribution-shift","title":"Fairness Violations and Mitigation under Covariate Shift","date":"2019-11-02","arxiv_id":"1911.00677","n_code_links":0,"syntology":null},{"paper":null,"slug":"fuzzy-inference-procedure-for-intelligent-and","title":"Fuzzy Inference Procedure for Intelligent and Automated Control of Refrigerant Charging","date":"2019-11-02","arxiv_id":"1911.02514","n_code_links":0,"syntology":null},{"paper":null,"slug":"model-specification-test-with-unlabeled-data","title":"Model Specification Test with Unlabeled Data: Approach from Covariate Shift","date":"2019-11-02","arxiv_id":"1911.00688","n_code_links":0,"syntology":null},{"paper":null,"slug":"on-modelling-label-uncertainty-in-deep-neural","title":"On Modelling Label Uncertainty in Deep Neural Networks: Automatic Estimation of Intra-observer Variability in 2D Echocardiography Quality Assessment","date":"2019-11-02","arxiv_id":"1911.00674","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-system-for-diacritizing-four-varieties-of","title":"A System for Diacritizing Four Varieties of Arabic","date":"2019-11-01","arxiv_id":null,"n_code_links":0,"syntology":null}],"record_sha256":"592b0f81b4628947f0c472d3ca20e7325fd89a6d9c27ee8397c636a61bb85137","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}