{"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":"/task/deep-learning/papers/74","list_of":"/task/deep-learning","task":"Deep Learning","archive":{"snapshot":"2025-07-28"},"key_notes":{"n_ran_checked":"legacy name, kept unchanged so existing readers do not break: it counts the samples that ran with no instrument failure (honoured, violated, and ran with no contract checked); it does not mean a contract was checked, and the pages print it as 'K with no instrument failure', not 'K checked'","n_constructed":"a sub-count of the samples that ran, never subtracted from them and never a failure: an executed sample whose run returned an instance of its own class (fixture_out_type equals the entry name): the run built an object and did not compute a result (Syntology's RAN record, counts.constructed)"},"syntology_read_at":"2026-09-28T10:30:06+00:00","order":"archive","order_definition":"repositories listed in the archive (most first), then date (newest first), then slug","page":74,"pages_in_order":95,"rows_per_page":100,"rows":[7301,7400],"of":9423,"counts":{"archive_papers_tagged":9423,"with_a_code_link":2693,"where_syntology_ran_a_sample":410,"not_listed_spam_title":0,"listed":9423,"listed_where_code_ran":410,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":356,"every_run_a_failure_of_syntologys_instrument":54,"listed_with_a_run_with_no_instrument_failure":356,"listed_every_run_a_failure_of_syntologys_instrument":54,"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":"/task/deep-learning","prev":"/task/deep-learning/papers/73","next":"/task/deep-learning/papers/75","papers":[{"url":null,"slug":"a-review-of-multi-objective-deep-learning","title":"A Review of Multi-Objective Deep Learning Speech Denoising Methods","date":"2020-03-26","arxiv_id":"2003.12108","repositories_listed":0,"syntology":null},{"url":null,"slug":"interpretable-deep-learning-model-for-online","title":"Interpretable Deep Learning Model for Online Multi-touch Attribution","date":"2020-03-26","arxiv_id":"2004.00384","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-on-knowledge-graph-for","title":"Deep Learning on Knowledge Graph for Recommender System: A Survey","date":"2020-03-25","arxiv_id":"2004.00387","repositories_listed":0,"syntology":null},{"url":null,"slug":"plausible-counterfactuals-auditing-deep","title":"Plausible Counterfactuals: Auditing Deep Learning Classifiers with Realistic Adversarial Examples","date":"2020-03-25","arxiv_id":"2003.11323","repositories_listed":0,"syntology":null},{"url":null,"slug":"tractogram-filtering-of-anatomically-non","title":"Tractogram filtering of anatomically non-plausible fibers with geometric deep learning","date":"2020-03-24","arxiv_id":"2003.11013","repositories_listed":0,"syntology":null},{"url":null,"slug":"cf2-net-coarse-to-fine-fusion-convolutional","title":"CF2-Net: Coarse-to-Fine Fusion Convolutional Network for Breast Ultrasound Image Segmentation","date":"2020-03-23","arxiv_id":"2003.10144","repositories_listed":0,"syntology":null},{"url":null,"slug":"audio-impairment-recognition-using-a","title":"Audio Impairment Recognition Using a Correlation-Based Feature Representation","date":"2020-03-22","arxiv_id":"2003.09889","repositories_listed":0,"syntology":null},{"url":null,"slug":"estimating-uncertainty-and-interpretability","title":"Estimating Uncertainty and Interpretability in Deep Learning for Coronavirus (COVID-19) Detection","date":"2020-03-22","arxiv_id":"2003.10769","repositories_listed":0,"syntology":null},{"url":null,"slug":"single-shot-autofocusing-of-microscopy-images","title":"Single-shot autofocusing of microscopy images using deep learning","date":"2020-03-21","arxiv_id":"2003.09585","repositories_listed":0,"syntology":null},{"url":null,"slug":"imagination-augmented-deep-learning-for-goal","title":"Imagination-Augmented Deep Learning for Goal Recognition","date":"2020-03-20","arxiv_id":"2003.09529","repositories_listed":0,"syntology":null},{"url":null,"slug":"inverse-problems-deep-learning-and-symmetry","title":"Inverse Problems, Deep Learning, and Symmetry Breaking","date":"2020-03-20","arxiv_id":"2003.09077","repositories_listed":0,"syntology":null},{"url":null,"slug":"investigating-image-applications-based-on","title":"Investigating Image Applications Based on Spatial-Frequency Transform and Deep Learning Techniques","date":"2020-03-20","arxiv_id":"2004.02756","repositories_listed":0,"syntology":null},{"url":null,"slug":"data-science-in-economics","title":"Data Science in Economics","date":"2020-03-19","arxiv_id":"2003.13422","repositories_listed":0,"syntology":null},{"url":null,"slug":"extremal-region-analysis-based-deep-learning","title":"Extremal Region Analysis based Deep Learning Framework for Detecting Defects","date":"2020-03-19","arxiv_id":"2003.08525","repositories_listed":0,"syntology":null},{"url":null,"slug":"quality-control-of-neuron-reconstruction","title":"Quality Control of Neuron Reconstruction Based on Deep Learning","date":"2020-03-19","arxiv_id":"2003.08556","repositories_listed":0,"syntology":null},{"url":null,"slug":"unsupervised-text-line-segmentation","title":"Unsupervised deep learning for text line segmentation","date":"2020-03-19","arxiv_id":"2003.08632","repositories_listed":0,"syntology":null},{"url":null,"slug":"eisen-a-python-package-for-solid-deep","title":"Eisen: a python package for solid deep learning","date":"2020-03-18","arxiv_id":"2004.02747","repositories_listed":0,"syntology":null},{"url":null,"slug":"teacher-student-domain-adaptation-for","title":"Teacher-Student Domain Adaptation for Biosensor Models","date":"2020-03-17","arxiv_id":"2003.07896","repositories_listed":0,"syntology":null},{"url":null,"slug":"anomalous-instance-detection-in-deep-learning","title":"Anomalous Example Detection in Deep Learning: A Survey","date":"2020-03-16","arxiv_id":"2003.06979","repositories_listed":0,"syntology":null},{"url":null,"slug":"developing-a-recommendation-benchmark-for","title":"Developing a Recommendation Benchmark for MLPerf Training and Inference","date":"2020-03-16","arxiv_id":"2003.07336","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-cnn-lstm-model-for-gold-price-time-series","title":"A CNN–LSTM model for gold price time-series forecasting","date":"2020-03-14","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"monocular-depth-estimation-based-on-deep","title":"Monocular Depth Estimation Based On Deep Learning: An Overview","date":"2020-03-14","arxiv_id":"2003.06620","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-based-sequential-pattern-mining","title":"Deep learning-based sequential pattern mining for progressive database","date":"2020-03-13","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"mass-estimation-of-galaxy-clusters-with-deep","title":"Mass Estimation of Galaxy Clusters with Deep Learning I: Sunyaev-Zel'dovich Effect","date":"2020-03-13","arxiv_id":"2003.06135","repositories_listed":0,"syntology":null},{"url":null,"slug":"rssi-based-hybrid-beamforming-design-with","title":"RSSI-Based Hybrid Beamforming Design with Deep Learning","date":"2020-03-12","arxiv_id":"2003.06042","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-precisely-xtreme-multi-channel-hybrid","title":"A Precisely Xtreme-Multi Channel Hybrid Approach For Roman Urdu Sentiment Analysis","date":"2020-03-11","arxiv_id":"2003.05443","repositories_listed":0,"syntology":null},{"url":null,"slug":"communication-efficient-distributed-deep","title":"Communication-Efficient Distributed Deep Learning: A Comprehensive Survey","date":"2020-03-10","arxiv_id":"2003.06307","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-approach-for-breast-cancer","title":"Deep learning approach for breast cancer diagnosis","date":"2020-03-10","arxiv_id":"2003.04480","repositories_listed":0,"syntology":null},{"url":null,"slug":"pnp-net-a-hybrid-perspective-n-point-network","title":"PnP-Net: A hybrid Perspective-n-Point Network","date":"2020-03-10","arxiv_id":"2003.04626","repositories_listed":0,"syntology":null},{"url":null,"slug":"robustness-study-of-noisy-annotation-in-deep","title":"Robustness study of noisy annotation in deep learning based medical image segmentation","date":"2020-03-10","arxiv_id":"2003.06240","repositories_listed":0,"syntology":null},{"url":null,"slug":"utilizing-deep-learning-to-identify-drug-use","title":"Utilizing Deep Learning to Identify Drug Use on Twitter Data","date":"2020-03-08","arxiv_id":"2003.11522","repositories_listed":0,"syntology":null},{"url":null,"slug":"endoscopy-disease-detection-challenge-2020","title":"Endoscopy disease detection challenge 2020","date":"2020-03-07","arxiv_id":"2003.03376","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-for-prediction-of-population","title":"Deep learning for prediction of population health costs","date":"2020-03-06","arxiv_id":"2003.03466","repositories_listed":0,"syntology":null},{"url":null,"slug":"traffic-signs-detection-and-recognition","title":"Traffic Signs Detection and Recognition System using Deep Learning","date":"2020-03-06","arxiv_id":"2003.03256","repositories_listed":0,"syntology":null},{"url":"/paper/plant-disease-detection-from-images","slug":"plant-disease-detection-from-images","title":"Plant Disease Detection from Images","date":"2020-03-05","arxiv_id":"2003.05379","repositories_listed":0,"syntology":null},{"url":null,"slug":"pruning-filters-while-training-for","title":"Pruning Filters while Training for Efficiently Optimizing Deep Learning Networks","date":"2020-03-05","arxiv_id":"2003.02800","repositories_listed":0,"syntology":null},{"url":null,"slug":"search-space-of-adversarial-perturbations","title":"Search Space of Adversarial Perturbations against Image Filters","date":"2020-03-05","arxiv_id":"2003.02750","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-neural-network-perception-models-and","title":"Deep Neural Network Perception Models and Robust Autonomous Driving Systems","date":"2020-03-04","arxiv_id":"2003.08756","repositories_listed":0,"syntology":null},{"url":null,"slug":"touch-the-wind-simultaneous-airflow-drag-and","title":"Touch the Wind: Simultaneous Airflow, Drag and Interaction Sensing on a Multirotor","date":"2020-03-04","arxiv_id":"2003.02305","repositories_listed":0,"syntology":null},{"url":null,"slug":"benchmark-performance-of-machine-and-deep","title":"Benchmark Performance of Machine And Deep Learning Based Methodologies for Urdu Text Document Classification","date":"2020-03-03","arxiv_id":"2003.01345","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-in-memristive-nanowire-networks","title":"Deep Learning in Memristive Nanowire Networks","date":"2020-03-03","arxiv_id":"2003.02642","repositories_listed":0,"syntology":null},{"url":null,"slug":"deepmal-deep-learning-models-for-malware","title":"DeepMAL -- Deep Learning Models for Malware Traffic Detection and Classification","date":"2020-03-03","arxiv_id":"2003.04079","repositories_listed":0,"syntology":null},{"url":null,"slug":"overall-error-analysis-for-the-training-of","title":"Overall error analysis for the training of deep neural networks via stochastic gradient descent with random initialisation","date":"2020-03-03","arxiv_id":"2003.01291","repositories_listed":0,"syntology":null},{"url":null,"slug":"explainable-and-scalable-machine-learning","title":"Explainable and Scalable Machine-Learning Algorithms for Detection of Autism Spectrum Disorder using fMRI Data","date":"2020-03-02","arxiv_id":"2003.01541","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-deep-learning-framework-for-optimization-of-1","title":"A Deep Learning Framework for Optimization of MISO Downlink Beamforming","date":"2020-03-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-for-musculoskeletal-image","title":"Deep Learning for Musculoskeletal Image Analysis","date":"2020-03-01","arxiv_id":"2003.00541","repositories_listed":0,"syntology":null},{"url":null,"slug":"differentially-private-deep-learning-with","title":"Differentially Private Deep Learning with Smooth Sensitivity","date":"2020-03-01","arxiv_id":"2003.00505","repositories_listed":0,"syntology":null},{"url":null,"slug":"the-sloop-system-for-individual-animal","title":"The Sloop System for Individual Animal Identification with Deep Learning","date":"2020-03-01","arxiv_id":"2003.00559","repositories_listed":0,"syntology":null},{"url":null,"slug":"introduction-to-deep-learning","title":"Introduction to deep learning","date":"2020-02-29","arxiv_id":"2003.03253","repositories_listed":0,"syntology":null},{"url":null,"slug":"quantum-computing-assisted-deep-learning-for","title":"Quantum Computing Assisted Deep Learning for Fault Detection and Diagnosis in Industrial Process Systems","date":"2020-02-29","arxiv_id":"2003.00264","repositories_listed":0,"syntology":null},{"url":null,"slug":"applying-tensor-decomposition-to-image-for","title":"Applying Tensor Decomposition to image for Robustness against Adversarial Attack","date":"2020-02-28","arxiv_id":"2002.12913","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-in-mining-biological-data","title":"Deep Learning in Mining Biological Data","date":"2020-02-28","arxiv_id":"2003.00108","repositories_listed":0,"syntology":null},{"url":null,"slug":"do-optimization-methods-in-deep-learning","title":"Do optimization methods in deep learning applications matter?","date":"2020-02-28","arxiv_id":"2002.12642","repositories_listed":0,"syntology":null},{"url":null,"slug":"improved-image-coding-autoencoder-with-deep","title":"Improved Image Coding Autoencoder With Deep Learning","date":"2020-02-28","arxiv_id":"2002.12521","repositories_listed":0,"syntology":null},{"url":null,"slug":"review-noise-and-artifact-reduction-for-mri","title":"Review: Noise and artifact reduction for MRI using deep learning","date":"2020-02-28","arxiv_id":"2002.12889","repositories_listed":0,"syntology":null},{"url":null,"slug":"bridging-the-gap-between-spatial-and-spectral","title":"Bridging the Gap between Spatial and Spectral Domains: A Survey on Graph Neural Networks","date":"2020-02-27","arxiv_id":"2002.11867","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-on-radar-centric-3d-object","title":"Deep Learning on Radar Centric 3D Object Detection","date":"2020-02-27","arxiv_id":"2003.00851","repositories_listed":0,"syntology":null},{"url":null,"slug":"time-series-data-augmentation-for-deep","title":"Time Series Data Augmentation for Deep Learning: A Survey","date":"2020-02-27","arxiv_id":"2002.12478","repositories_listed":0,"syntology":null},{"url":null,"slug":"assessing-graph-based-deep-learning-models","title":"Assessing Graph-based Deep Learning Models for Predicting Flash Point","date":"2020-02-26","arxiv_id":"2002.11315","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-and-statistical-models-for-time","title":"Deep Learning and Statistical Models for Time-Critical Pedestrian Behaviour Prediction","date":"2020-02-26","arxiv_id":"2002.11226","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-based-cell-parasites-detection","title":"ParasNet: Fast Parasites Detection with Neural Networks","date":"2020-02-26","arxiv_id":"2002.11327","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-for-biomedical-image","title":"Deep Learning for Biomedical Image Reconstruction: A Survey","date":"2020-02-26","arxiv_id":"2002.12351","repositories_listed":0,"syntology":null},{"url":null,"slug":"dlspec-a-deep-learning-task-exchange","title":"DLSpec: A Deep Learning Task Exchange Specification","date":"2020-02-26","arxiv_id":"2002.11262","repositories_listed":0,"syntology":null},{"url":null,"slug":"embedding-hard-physical-constraints-in","title":"Embedding Hard Physical Constraints in Convolutional Neural Networks for 3D Turbulence","date":"2020-02-26","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"improving-robustness-of-deep-learning-based-1","title":"Improving Robustness of Deep-Learning-Based Image Reconstruction","date":"2020-02-26","arxiv_id":"2002.11821","repositories_listed":0,"syntology":null},{"url":null,"slug":"tensor-decompositions-in-deep-learning","title":"Tensor Decompositions in Deep Learning","date":"2020-02-26","arxiv_id":"2002.11835","repositories_listed":0,"syntology":null},{"url":null,"slug":"uncertainty-quantification-for-sparse-deep","title":"Uncertainty Quantification for Sparse Deep Learning","date":"2020-02-26","arxiv_id":"2002.11815","repositories_listed":0,"syntology":null},{"url":null,"slug":"coherent-gradients-an-approach-to-1","title":"Coherent Gradients: An Approach to Understanding Generalization in Gradient Descent-based Optimization","date":"2020-02-25","arxiv_id":"2002.10657","repositories_listed":0,"syntology":null},{"url":null,"slug":"iot-device-identification-using-deep-learning","title":"IoT Device Identification Using Deep Learning","date":"2020-02-25","arxiv_id":"2002.11686","repositories_listed":0,"syntology":null},{"url":null,"slug":"very-simple-statistical-evidence-that-alphago","title":"Very simple statistical evidence that AlphaGo has exceeded human limits in playing GO game","date":"2020-02-25","arxiv_id":"2002.11107","repositories_listed":0,"syntology":null},{"url":null,"slug":"communication-contention-aware-scheduling-of","title":"Communication Contention Aware Scheduling of Multiple Deep Learning Training Jobs","date":"2020-02-24","arxiv_id":"2002.10105","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-predicts-total-knee-replacement","title":"Deep learning predicts total knee replacement from magnetic resonance images","date":"2020-02-24","arxiv_id":"2002.10591","repositories_listed":0,"syntology":null},{"url":null,"slug":"regression-with-deep-learning-for-sensor","title":"Regression with Deep Learning for Sensor Performance Optimization","date":"2020-02-22","arxiv_id":"2002.11044","repositories_listed":0,"syntology":null},{"url":null,"slug":"sampling-for-deep-learning-model-diagnosis","title":"Sampling for Deep Learning Model Diagnosis (Technical Report)","date":"2020-02-22","arxiv_id":"2002.09754","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-system-to-screen-coronavirus","title":"Deep Learning System to Screen Coronavirus Disease 2019 Pneumonia","date":"2020-02-21","arxiv_id":"2002.09334","repositories_listed":0,"syntology":null},{"url":null,"slug":"introducing-fuzzy-layers-for-deep-learning","title":"Introducing Fuzzy Layers for Deep Learning","date":"2020-02-21","arxiv_id":"2003.00880","repositories_listed":0,"syntology":null},{"url":null,"slug":"comparing-different-deep-learning","title":"Comparing Different Deep Learning Architectures for Classification of Chest Radiographs","date":"2020-02-20","arxiv_id":"2002.08991","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-multi-facial-patches-aggregation-network","title":"Deep Multi-Facial Patches Aggregation Network For Facial Expression Recognition","date":"2020-02-20","arxiv_id":"2002.09298","repositories_listed":0,"syntology":null},{"url":null,"slug":"unsupervised-pre-trained-texture-aware-and","title":"Unsupervised Pre-trained, Texture Aware And Lightweight Model for Deep Learning-Based Iris Recognition Under Limited Annotated Data","date":"2020-02-20","arxiv_id":"2002.09048","repositories_listed":0,"syntology":null},{"url":null,"slug":"neural-architecture-search-for-fault","title":"Neural Architecture Search For Fault Diagnosis","date":"2020-02-19","arxiv_id":"2002.07997","repositories_listed":0,"syntology":null},{"url":null,"slug":"tourism-demand-forecasting-with-tourist","title":"Tourism Demand Forecasting: An Ensemble Deep Learning Approach","date":"2020-02-19","arxiv_id":"2002.07964","repositories_listed":0,"syntology":null},{"url":null,"slug":"block-switching-a-stochastic-approach-for","title":"Block Switching: A Stochastic Approach for Deep Learning Security","date":"2020-02-18","arxiv_id":"2002.07920","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-approaches-for-open-set","title":"Deep Learning Approaches for Open Set Wireless Transmitter Authorization","date":"2020-02-18","arxiv_id":"2002.07777","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-in-medical-ultrasound-image","title":"Deep Learning in Medical Ultrasound Image Segmentation: a Review","date":"2020-02-18","arxiv_id":"2002.07703","repositories_listed":0,"syntology":null},{"url":null,"slug":"workshop-report-detection-and-classification","title":"Workshop Report: Detection and Classification in Marine Bioacoustics with Deep Learning","date":"2020-02-18","arxiv_id":"2002.08249","repositories_listed":0,"syntology":null},{"url":null,"slug":"evolutionary-optimization-of-deep-learning","title":"Evolutionary Optimization of Deep Learning Activation Functions","date":"2020-02-17","arxiv_id":"2002.07224","repositories_listed":0,"syntology":null},{"url":null,"slug":"photonic-convolutional-neural-networks-using","title":"Photonic convolutional neural networks using integrated diffractive optics","date":"2020-02-17","arxiv_id":"2003.12015","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-for-asset-bubbles-detection","title":"Deep Learning for Asset Bubbles Detection","date":"2020-02-15","arxiv_id":"2002.06405","repositories_listed":0,"syntology":null},{"url":null,"slug":"deephe-accurately-predicting-human-essential","title":"DeepHE: Accurately Predicting Human Essential Genes based on Deep Learning","date":"2020-02-15","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"monotonic-cardinality-estimation-of","title":"Monotonic Cardinality Estimation of Similarity Selection: A Deep Learning Approach","date":"2020-02-15","arxiv_id":"2002.06442","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-survey-on-3d-skeleton-based-action","title":"A Survey on 3D Skeleton-Based Action Recognition Using Learning Method","date":"2020-02-14","arxiv_id":"2002.05907","repositories_listed":0,"syntology":null},{"url":null,"slug":"accurate-stress-assessment-based-on","title":"Accurate Stress Assessment based on functional Near Infrared Spectroscopy using Deep Learning Approach","date":"2020-02-14","arxiv_id":"2002.06282","repositories_listed":0,"syntology":null},{"url":null,"slug":"admm-based-decoder-for-binary-linear-codes","title":"ADMM-based Decoder for Binary Linear Codes Aided by Deep Learning","date":"2020-02-14","arxiv_id":"2002.07601","repositories_listed":0,"syntology":null},{"url":null,"slug":"verifying-deep-learning-based-decisions-for","title":"Verifying Deep Learning-based Decisions for Facial Expression Recognition","date":"2020-02-14","arxiv_id":"2003.00828","repositories_listed":0,"syntology":null},{"url":null,"slug":"learnable-bernoulli-dropout-for-bayesian-deep","title":"Learnable Bernoulli Dropout for Bayesian Deep Learning","date":"2020-02-12","arxiv_id":"2002.05155","repositories_listed":0,"syntology":null},{"url":null,"slug":"the-unreasonable-effectiveness-of-deep-2","title":"The Unreasonable Effectiveness of Deep Learning in Artificial Intelligence","date":"2020-02-12","arxiv_id":"2002.04806","repositories_listed":0,"syntology":null},{"url":null,"slug":"optimal-transfer-learning-model-for-binary","title":"Optimal Transfer Learning Model for Binary Classification of Funduscopic Images through Simple Heuristics","date":"2020-02-11","arxiv_id":"2002.04189","repositories_listed":0,"syntology":null},{"url":null,"slug":"advances-in-deep-space-exploration-via","title":"Advances in Deep Space Exploration via Simulators & Deep Learning","date":"2020-02-10","arxiv_id":"2002.04051","repositories_listed":0,"syntology":null},{"url":null,"slug":"feature-level-malware-obfuscation-in-deep","title":"Feature-level Malware Obfuscation in Deep Learning","date":"2020-02-10","arxiv_id":"2002.05517","repositories_listed":0,"syntology":null},{"url":null,"slug":"improving-deep-learning-for-airbnb-search","title":"Improving Deep Learning For Airbnb Search","date":"2020-02-10","arxiv_id":"2002.05515","repositories_listed":0,"syntology":null}],"record_sha256":"e49cacd456e71203519e68470c048f3b2fcf3ae49ec54004cde5e113239ab72d","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}