{"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/34","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":34,"pages_in_order":65,"rows_per_page":100,"rows":[3301,3400],"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/33","next":"/method/test/papers/35","papers":[{"paper":"/paper/dpnet-dual-path-network-for-real-time-object","slug":"dpnet-dual-path-network-for-real-time-object","title":"DPNet: Dual-Path Network for Real-time Object Detection with Lightweight Attention","date":"2022-09-28","arxiv_id":"2209.13933","n_code_links":2,"syntology":null},{"paper":null,"slug":"effective-general-domain-data-inclusion-for","title":"Effective General-Domain Data Inclusion for the Machine Translation Task by Vanilla Transformers","date":"2022-09-28","arxiv_id":"2209.14073","n_code_links":0,"syntology":null},{"paper":null,"slug":"identifying-differential-equations-to-predict","title":"Identifying Differential Equations to predict Blood Glucose using Sparse Identification of Nonlinear Systems","date":"2022-09-28","arxiv_id":"2209.13852","n_code_links":0,"syntology":null},{"paper":null,"slug":"improving-text-to-sql-semantic-parsing-with","title":"Improving Text-to-SQL Semantic Parsing with Fine-grained Query Understanding","date":"2022-09-28","arxiv_id":"2209.14415","n_code_links":0,"syntology":null},{"paper":null,"slug":"machine-learning-for-optical-motion-capture","title":"Machine Learning for Optical Motion Capture-driven Musculoskeletal Modelling from Inertial Motion Capture Data","date":"2022-09-28","arxiv_id":"2209.14456","n_code_links":0,"syntology":null},{"paper":null,"slug":"on-the-visual-analytic-intelligence-of-neural","title":"On the visual analytic intelligence of neural networks","date":"2022-09-28","arxiv_id":"2209.14017","n_code_links":0,"syntology":null},{"paper":"/paper/transfer-learning-with-pretrained-remote","slug":"transfer-learning-with-pretrained-remote","title":"Transfer Learning with Pretrained Remote Sensing Transformers","date":"2022-09-28","arxiv_id":"2209.14969","n_code_links":1,"syntology":null},{"paper":null,"slug":"using-contradictions-to-improve-qa-systems","title":"Using contradictions improves question answering systems","date":"2022-09-28","arxiv_id":"2211.05598","n_code_links":0,"syntology":null},{"paper":null,"slug":"verifying-safety-of-behaviour-trees-in-event","title":"Verifying Safety of Behaviour Trees in Event-B","date":"2022-09-28","arxiv_id":"2209.14045","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-comparative-study-of-attention-mechanism","title":"A comparative study of attention mechanism and generative adversarial network in facade damage segmentation","date":"2022-09-27","arxiv_id":"2209.13283","n_code_links":0,"syntology":null},{"paper":"/paper/adafocusv3-on-unified-spatial-temporal","slug":"adafocusv3-on-unified-spatial-temporal","title":"AdaFocusV3: On Unified Spatial-temporal Dynamic Video Recognition","date":"2022-09-27","arxiv_id":"2209.13465","n_code_links":1,"syntology":null},{"paper":null,"slug":"bayesnetcnn-incorporating-uncertainty-in","title":"BayesNetCNN: incorporating uncertainty in neural networks for image-based classification tasks","date":"2022-09-27","arxiv_id":"2209.13096","n_code_links":0,"syntology":null},{"paper":null,"slug":"beyond-heart-murmur-detection-automatic","title":"Beyond Heart Murmur Detection: Automatic Murmur Grading from Phonocardiogram","date":"2022-09-27","arxiv_id":"2209.13385","n_code_links":0,"syntology":null},{"paper":null,"slug":"design-of-experiments-for-the-calibration-of","title":"Design of experiments for the calibration of history-dependent models via deep reinforcement learning and an enhanced Kalman filter","date":"2022-09-27","arxiv_id":"2209.13126","n_code_links":0,"syntology":null},{"paper":"/paper/explainable-global-fairness-verification-of","slug":"explainable-global-fairness-verification-of","title":"Explainable Global Fairness Verification of Tree-Based Classifiers","date":"2022-09-27","arxiv_id":"2209.13179","n_code_links":1,"syntology":null},{"paper":"/paper/formal-conceptual-views-in-neural-networks","slug":"formal-conceptual-views-in-neural-networks","title":"Formal Conceptual Views in Neural Networks","date":"2022-09-27","arxiv_id":"2209.13517","n_code_links":1,"syntology":null},{"paper":null,"slug":"from-ranked-lists-to-carousels-a-carousel","title":"From Ranked Lists to Carousels: A Carousel Click Model","date":"2022-09-27","arxiv_id":"2209.13426","n_code_links":0,"syntology":null},{"paper":"/paper/globally-optimal-event-based-divergence","slug":"globally-optimal-event-based-divergence","title":"Globally Optimal Event-Based Divergence Estimation for Ventral Landing","date":"2022-09-27","arxiv_id":"2209.13168","n_code_links":1,"syntology":null},{"paper":"/paper/im2oil-stroke-based-oil-painting-rendering","slug":"im2oil-stroke-based-oil-painting-rendering","title":"Im2Oil: Stroke-Based Oil Painting Rendering with Linearly Controllable Fineness Via Adaptive Sampling","date":"2022-09-27","arxiv_id":"2209.13219","n_code_links":1,"syntology":null},{"paper":null,"slug":"measuring-overfitting-in-convolutional-neural","title":"Measuring Overfitting in Convolutional Neural Networks using Adversarial Perturbations and Label Noise","date":"2022-09-27","arxiv_id":"2209.13382","n_code_links":0,"syntology":null},{"paper":null,"slug":"statistical-limits-of-correlation-detection","title":"Statistical limits of correlation detection in trees","date":"2022-09-27","arxiv_id":"2209.13723","n_code_links":0,"syntology":null},{"paper":null,"slug":"towards-regression-free-neural-networks-for","title":"Towards Regression-Free Neural Networks for Diverse Compute Platforms","date":"2022-09-27","arxiv_id":"2209.13740","n_code_links":0,"syntology":null},{"paper":"/paper/v2xp-asg-generating-adversarial-scenes-for","slug":"v2xp-asg-generating-adversarial-scenes-for","title":"V2XP-ASG: Generating Adversarial Scenes for Vehicle-to-Everything Perception","date":"2022-09-27","arxiv_id":"2209.13679","n_code_links":1,"syntology":null},{"paper":null,"slug":"when-handcrafted-features-and-deep-features","title":"When Handcrafted Features and Deep Features Meet Mismatched Training and Test Sets for Deepfake Detection","date":"2022-09-27","arxiv_id":"2209.13289","n_code_links":0,"syntology":null},{"paper":null,"slug":"featurebox-feature-engineering-on-gpus-for","title":"FeatureBox: Feature Engineering on GPUs for Massive-Scale Ads Systems","date":"2022-09-26","arxiv_id":"2210.07768","n_code_links":0,"syntology":null},{"paper":null,"slug":"investigating-self-supervised-learning-for-1","title":"End-to-End Lyrics Recognition with Self-supervised Learning","date":"2022-09-26","arxiv_id":"2209.12702","n_code_links":0,"syntology":null},{"paper":"/paper/it-takes-two-learning-to-plan-for-human-robot","slug":"it-takes-two-learning-to-plan-for-human-robot","title":"It Takes Two: Learning to Plan for Human-Robot Cooperative Carrying","date":"2022-09-26","arxiv_id":"2209.12890","n_code_links":2,"syntology":{"ran":5,"of":13,"n_ran_checked":5,"n_instrument":0,"unverified":8,"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) · 8 unverified","official":{"repos":["eleyng/table-carrying-ai","eleyng/cooperative_planner"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":8,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"learning-critical-scenarios-in-feedback","title":"Learning Critical Scenarios in Feedback Control Systems for Automated Driving","date":"2022-09-26","arxiv_id":"2209.12586","n_code_links":0,"syntology":null},{"paper":"/paper/learning-to-learn-with-generative-models-of","slug":"learning-to-learn-with-generative-models-of","title":"Learning to Learn with Generative Models of Neural Network Checkpoints","date":"2022-09-26","arxiv_id":"2209.12892","n_code_links":1,"syntology":{"ran":16,"of":20,"n_ran_checked":15,"n_instrument":1,"unverified":4,"pointer_only":1,"phrase":"16 ran (of which 0 constructed an object rather than computing a result; 15 with no instrument failure: 0 honoured, 0 violated, 15 with no contract checked; 1 where Syntology's instrument failed) · 4 unverified","official":{"repos":["wpeebles/g.pt"],"state":"official (archive's flag): 16 ran","n_ran":16,"n_constructed":0,"n_ran_no_instrument_failure":15,"n_unverified":4,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"molecular-dynamics-simulations-with-grand","title":"Molecular dynamics simulations with grand-canonical reweighting suggest cooperativity effects in RNA structure probing experiments","date":"2022-09-26","arxiv_id":"2209.12640","n_code_links":0,"syntology":null},{"paper":"/paper/news-summarization-and-evaluation-in-the-era","slug":"news-summarization-and-evaluation-in-the-era","title":"News Summarization and Evaluation in the Era of GPT-3","date":"2022-09-26","arxiv_id":"2209.12356","n_code_links":1,"syntology":null},{"paper":"/paper/out-of-distribution-detection-with-hilbert","slug":"out-of-distribution-detection-with-hilbert","title":"Out-of-Distribution Detection with Hilbert-Schmidt Independence Optimization","date":"2022-09-26","arxiv_id":"2209.12807","n_code_links":1,"syntology":null},{"paper":"/paper/power-system-anomaly-detection-and","slug":"power-system-anomaly-detection-and","title":"Power System Anomaly Detection and Classification Utilizing WLS-EKF State Estimation and Machine Learning","date":"2022-09-26","arxiv_id":"2209.12629","n_code_links":1,"syntology":null},{"paper":"/paper/prayatul-matrix-a-direct-comparison-approach","slug":"prayatul-matrix-a-direct-comparison-approach","title":"Prayatul Matrix: A Direct Comparison Approach to Evaluate Performance of Supervised Machine Learning Models","date":"2022-09-26","arxiv_id":"2209.12728","n_code_links":1,"syntology":null},{"paper":null,"slug":"stempo-dynamic-x-ray-tomography-phantom","title":"STEMPO -- dynamic X-ray tomography phantom","date":"2022-09-26","arxiv_id":"2209.12471","n_code_links":0,"syntology":null},{"paper":null,"slug":"towards-fine-dining-recipe-generation-with","title":"Towards Fine-Dining Recipe Generation with Generative Pre-trained Transformers","date":"2022-09-26","arxiv_id":"2209.12774","n_code_links":0,"syntology":null},{"paper":"/paper/towards-parameter-efficient-integration-of","slug":"towards-parameter-efficient-integration-of","title":"Towards Parameter-Efficient Integration of Pre-Trained Language Models In Temporal Video Grounding","date":"2022-09-26","arxiv_id":"2209.13359","n_code_links":1,"syntology":null},{"paper":null,"slug":"variationally-mimetic-operator-networks","title":"Variationally Mimetic Operator Networks","date":"2022-09-26","arxiv_id":"2209.12871","n_code_links":0,"syntology":null},{"paper":null,"slug":"algorithms-that-approximate-data-removal-new","title":"Algorithms that Approximate Data Removal: New Results and Limitations","date":"2022-09-25","arxiv_id":"2209.12269","n_code_links":0,"syntology":null},{"paper":"/paper/anomaly-detection-in-aerial-videos-with","slug":"anomaly-detection-in-aerial-videos-with","title":"Anomaly Detection in Aerial Videos with Transformers","date":"2022-09-25","arxiv_id":"2209.13363","n_code_links":1,"syntology":null},{"paper":null,"slug":"can-we-automate-the-analysis-of-online-child","title":"Can We Automate the Analysis of Online Child Sexual Exploitation Discourse?","date":"2022-09-25","arxiv_id":"2209.12320","n_code_links":0,"syntology":null},{"paper":null,"slug":"neural-inhibition-during-speech-planning","title":"Neural inhibition during speech planning contributes to contrastive hyperarticulation","date":"2022-09-25","arxiv_id":"2209.12278","n_code_links":0,"syntology":null},{"paper":"/paper/on-representing-linear-programs-by-graph","slug":"on-representing-linear-programs-by-graph","title":"On Representing Linear Programs by Graph Neural Networks","date":"2022-09-25","arxiv_id":"2209.12288","n_code_links":1,"syntology":{"ran":1,"of":2,"n_ran_checked":1,"n_instrument":0,"unverified":1,"pointer_only":2,"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":{"repos":["liujl11git/GNN-LP"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"on-the-opportunities-and-challenges-of-using","title":"Opportunities and Challenges from Using Animal Videos in Reinforcement Learning for Navigation","date":"2022-09-25","arxiv_id":"2209.12347","n_code_links":0,"syntology":null},{"paper":null,"slug":"reward-learning-using-structural-motifs-in","title":"Reward Learning using Structural Motifs in Inverse Reinforcement Learning","date":"2022-09-25","arxiv_id":"2209.13489","n_code_links":0,"syntology":null},{"paper":null,"slug":"sentiment-analysis-on-inflation-after-covid","title":"Sentiment Analysis on Inflation after Covid-19","date":"2022-09-25","arxiv_id":"2209.14737","n_code_links":0,"syntology":null},{"paper":null,"slug":"solving-seismic-wave-equations-on-variable","title":"Solving Seismic Wave Equations on Variable Velocity Models with Fourier Neural Operator","date":"2022-09-25","arxiv_id":"2209.12340","n_code_links":0,"syntology":null},{"paper":null,"slug":"transfer-learning-for-self-supervised-blind","title":"Transfer learning for self-supervised, blind-spot seismic denoising","date":"2022-09-25","arxiv_id":"2209.12210","n_code_links":0,"syntology":null},{"paper":"/paper/vaesim-a-probabilistic-approach-for-self","slug":"vaesim-a-probabilistic-approach-for-self","title":"VAESim: A probabilistic approach for self-supervised prototype discovery","date":"2022-09-25","arxiv_id":"2209.12279","n_code_links":1,"syntology":null},{"paper":null,"slug":"concordance-based-survival-cobra-with","title":"Concordance based Survival Cobra with regression type weak learners","date":"2022-09-24","arxiv_id":"2209.11919","n_code_links":0,"syntology":null},{"paper":null,"slug":"domainatm-domain-adaptation-toolbox-for","title":"DomainATM: Domain Adaptation Toolbox for Medical Data Analysis","date":"2022-09-24","arxiv_id":"2209.11890","n_code_links":0,"syntology":null},{"paper":null,"slug":"hybrid-multimodal-fusion-for-humor-detection","title":"Hybrid Multimodal Fusion for Humor Detection","date":"2022-09-24","arxiv_id":"2209.11949","n_code_links":0,"syntology":null},{"paper":null,"slug":"open-ended-diverse-solution-discovery-with","title":"Open-Ended Diverse Solution Discovery with Regulated Behavior Patterns for Cross-Domain Adaptation","date":"2022-09-24","arxiv_id":"2209.12029","n_code_links":0,"syntology":null},{"paper":null,"slug":"optimal-dispatch-of-low-carbon-integrated","title":"Optimal dispatch of low-carbon integrated energy system considering nuclear heating and carbon trading","date":"2022-09-24","arxiv_id":"2209.12025","n_code_links":0,"syntology":null},{"paper":null,"slug":"removal-of-ocular-artifacts-in-eeg-using-deep","title":"Removal of Ocular Artifacts in EEG Using Deep Learning","date":"2022-09-24","arxiv_id":"2209.11980","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-neural-template-matching-method-to-detect","title":"A Neural Template Matching Method to Detect Knee Joint Areas","date":"2022-09-23","arxiv_id":"2209.11791","n_code_links":0,"syntology":null},{"paper":null,"slug":"comparison-of-synthetic-dataset-generation","title":"Comparison of synthetic dataset generation methods for medical intervention rooms using medical clothing detection as an example","date":"2022-09-23","arxiv_id":"2209.11493","n_code_links":0,"syntology":null},{"paper":null,"slug":"creating-compact-regions-of-social","title":"Creating Compact Regions of Social Determinants of Health","date":"2022-09-23","arxiv_id":"2209.11836","n_code_links":0,"syntology":null},{"paper":null,"slug":"differentiable-physics-enabled-closure","title":"Differentiable physics-enabled closure modeling for Burgers' turbulence","date":"2022-09-23","arxiv_id":"2209.11614","n_code_links":0,"syntology":null},{"paper":null,"slug":"k-sample-multiple-hypothesis-testing-for","title":"K-sample Multiple Hypothesis Testing for Signal Detection","date":"2022-09-23","arxiv_id":"2209.11438","n_code_links":0,"syntology":null},{"paper":"/paper/query-based-hard-image-retrieval-for-object","slug":"query-based-hard-image-retrieval-for-object","title":"Query-based Hard-Image Retrieval for Object Detection at Test Time","date":"2022-09-23","arxiv_id":"2209.11559","n_code_links":1,"syntology":null},{"paper":null,"slug":"soft-labeling-strategies-for-rapid-sub-typing","title":"Soft-labeling Strategies for Rapid Sub-Typing","date":"2022-09-23","arxiv_id":"2209.12684","n_code_links":0,"syntology":null},{"paper":null,"slug":"test-test-time-self-training-under","title":"TeST: Test-time Self-Training under Distribution Shift","date":"2022-09-23","arxiv_id":"2209.11459","n_code_links":0,"syntology":null},{"paper":null,"slug":"wide-area-geolocalization-with-a-limited","title":"Wide-Area Geolocalization with a Limited Field of View Camera","date":"2022-09-23","arxiv_id":"2209.11854","n_code_links":0,"syntology":null},{"paper":"/paper/calving-fronts-and-where-to-find-them-a","slug":"calving-fronts-and-where-to-find-them-a","title":"Calving fronts and where to find them: a benchmark dataset and methodology for automatic glacier calving front extraction from synthetic aperture radar imagery","date":"2022-09-22","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":"/paper/capsule-network-based-contrastive-learning-of","slug":"capsule-network-based-contrastive-learning-of","title":"Capsule Network based Contrastive Learning of Unsupervised Visual Representations","date":"2022-09-22","arxiv_id":"2209.11276","n_code_links":1,"syntology":null},{"paper":"/paper/challenges-in-visual-anomaly-detection-for","slug":"challenges-in-visual-anomaly-detection-for","title":"Challenges in Visual Anomaly Detection for Mobile Robots","date":"2022-09-22","arxiv_id":"2209.10995","n_code_links":1,"syntology":null},{"paper":null,"slug":"colonoscopy-landmark-detection-using-vision","title":"Colonoscopy Landmark Detection using Vision Transformers","date":"2022-09-22","arxiv_id":"2209.11304","n_code_links":0,"syntology":null},{"paper":"/paper/counterfactual-explanations-using","slug":"counterfactual-explanations-using","title":"Counterfactual Explanations Using Optimization With Constraint Learning","date":"2022-09-22","arxiv_id":"2209.10997","n_code_links":1,"syntology":null},{"paper":null,"slug":"embedding-assisted-attentional-deep-learning","title":"Embedding-Assisted Attentional Deep Learning for Real-World RF Fingerprinting of Bluetooth","date":"2022-09-22","arxiv_id":"2210.02897","n_code_links":0,"syntology":null},{"paper":"/paper/equivariant-transduction-through-invariant","slug":"equivariant-transduction-through-invariant","title":"Equivariant Transduction through Invariant Alignment","date":"2022-09-22","arxiv_id":"2209.10926","n_code_links":1,"syntology":null},{"paper":null,"slug":"forecasting-cryptocurrencies-log-returns-a","title":"Forecasting Cryptocurrencies Log-Returns: a LASSO-VAR and Sentiment Approach","date":"2022-09-22","arxiv_id":"2210.00883","n_code_links":0,"syntology":null},{"paper":"/paper/identity-aware-hand-mesh-estimation-and","slug":"identity-aware-hand-mesh-estimation-and","title":"Identity-Aware Hand Mesh Estimation and Personalization from RGB Images","date":"2022-09-22","arxiv_id":"2209.10840","n_code_links":1,"syntology":null},{"paper":"/paper/mlgwsc-1-the-first-machine-learning","slug":"mlgwsc-1-the-first-machine-learning","title":"MLGWSC-1: The first Machine Learning Gravitational-Wave Search Mock Data Challenge","date":"2022-09-22","arxiv_id":"2209.11146","n_code_links":1,"syntology":null},{"paper":null,"slug":"multiscale-comparison-of-nonparametric-trend","title":"Multiscale Comparison of Nonparametric Trend Curves","date":"2022-09-22","arxiv_id":"2209.10841","n_code_links":0,"syntology":null},{"paper":null,"slug":"simuships-a-high-resolution-simulation","title":"SimuShips -- A High Resolution Simulation Dataset for Ship Detection with Precise Annotations","date":"2022-09-22","arxiv_id":"2211.05237","n_code_links":0,"syntology":null},{"paper":null,"slug":"uncertainty-aware-perception-models-for-off","title":"Uncertainty-aware Perception Models for Off-road Autonomous Unmanned Ground Vehicles","date":"2022-09-22","arxiv_id":"2209.11115","n_code_links":0,"syntology":null},{"paper":"/paper/an-image-processing-approach-to-identify","slug":"an-image-processing-approach-to-identify","title":"An Image Processing approach to identify solar plages observed at 393.37 nm by the Kodaikanal Solar Observatory","date":"2022-09-21","arxiv_id":"2209.10631","n_code_links":1,"syntology":null},{"paper":"/paper/benchmarking-and-analyzing-3d-human-pose-and","slug":"benchmarking-and-analyzing-3d-human-pose-and","title":"Benchmarking and Analyzing 3D Human Pose and Shape Estimation Beyond Algorithms","date":"2022-09-21","arxiv_id":"2209.10529","n_code_links":1,"syntology":null},{"paper":"/paper/bias-at-a-second-glance-a-deep-dive-into-bias","slug":"bias-at-a-second-glance-a-deep-dive-into-bias","title":"Bias at a Second Glance: A Deep Dive into Bias for German Educational Peer-Review Data Modeling","date":"2022-09-21","arxiv_id":"2209.10335","n_code_links":2,"syntology":{"ran":3,"of":6,"n_ran_checked":3,"n_instrument":0,"unverified":3,"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) · 3 unverified","official":{"repos":["epfl-ml4ed/bias-at-a-second-glance"],"state":"official: harvested, nothing ran","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":3,"ran_from_kinds":["listed"]}}},{"paper":null,"slug":"data-driven-metaheuristic-based-off-grid","title":"Data-driven, metaheuristic-based off-grid microgrid capacity planning optimisation and scenario analysis: Insights from a case study of Aotea-Great Barrier Island","date":"2022-09-21","arxiv_id":"2209.10668","n_code_links":0,"syntology":null},{"paper":"/paper/deep-double-descent-via-smooth-interpolation","slug":"deep-double-descent-via-smooth-interpolation","title":"Deep Double Descent via Smooth Interpolation","date":"2022-09-21","arxiv_id":"2209.10080","n_code_links":1,"syntology":null},{"paper":"/paper/estimation-of-circular-statistics-in-the","slug":"estimation-of-circular-statistics-in-the","title":"Estimation of circular statistics in the presence of measurement bias","date":"2022-09-21","arxiv_id":"2209.10468","n_code_links":1,"syntology":null},{"paper":"/paper/improved-marginal-unbiased-score-expansion","slug":"improved-marginal-unbiased-score-expansion","title":"Improved Marginal Unbiased Score Expansion (MUSE) via Implicit Differentiation","date":"2022-09-21","arxiv_id":"2209.10512","n_code_links":1,"syntology":null},{"paper":null,"slug":"modeling-cognitive-load-as-a-self-supervised","title":"Modeling cognitive load as a self-supervised brain rate with electroencephalography and deep learning","date":"2022-09-21","arxiv_id":"2209.10992","n_code_links":0,"syntology":null},{"paper":null,"slug":"recurrent-super-resolution-method-for","title":"Recurrent Super-Resolution Method for Enhancing Low Quality Thermal Facial Data","date":"2022-09-21","arxiv_id":"2209.10489","n_code_links":0,"syntology":null},{"paper":null,"slug":"show-interpret-and-tell-entity-aware","title":"Show, Interpret and Tell: Entity-aware Contextualised Image Captioning in Wikipedia","date":"2022-09-21","arxiv_id":"2209.10474","n_code_links":0,"syntology":null},{"paper":null,"slug":"subject-verb-agreement-error-patterns-in","title":"Subject Verb Agreement Error Patterns in Meaningless Sentences: Humans vs. BERT","date":"2022-09-21","arxiv_id":"2209.10538","n_code_links":0,"syntology":null},{"paper":null,"slug":"the-returnzero-system-for-voxceleb-speaker","title":"The ReturnZero System for VoxCeleb Speaker Recognition Challenge 2022","date":"2022-09-21","arxiv_id":"2209.10147","n_code_links":0,"syntology":null},{"paper":null,"slug":"towards-real-time-thermal-simulations-for","title":"Towards Real Time Thermal Simulations for Design Optimization using Graph Neural Networks","date":"2022-09-21","arxiv_id":"2209.13348","n_code_links":0,"syntology":null},{"paper":"/paper/tree-methods-for-hierarchical-classification","slug":"tree-methods-for-hierarchical-classification","title":"Tree Methods for Hierarchical Classification in Parallel","date":"2022-09-21","arxiv_id":"2209.10288","n_code_links":2,"syntology":null},{"paper":"/paper/a-demonstration-of-over-the-air-computation","slug":"a-demonstration-of-over-the-air-computation","title":"A Demonstration of Over-the-Air Computation for Federated Edge Learning","date":"2022-09-20","arxiv_id":"2209.09954","n_code_links":1,"syntology":null},{"paper":"/paper/an-outlier-exposure-approach-to-improve","slug":"an-outlier-exposure-approach-to-improve","title":"An Outlier Exposure Approach to Improve Visual Anomaly Detection Performance for Mobile Robots","date":"2022-09-20","arxiv_id":"2209.09786","n_code_links":1,"syntology":null},{"paper":null,"slug":"calibrating-ensembles-for-scalable","title":"Calibrating Ensembles for Scalable Uncertainty Quantification in Deep Learning-based Medical Segmentation","date":"2022-09-20","arxiv_id":"2209.09563","n_code_links":0,"syntology":null},{"paper":"/paper/feature-embedding-in-click-through-rate","slug":"feature-embedding-in-click-through-rate","title":"Feature embedding in click-through rate prediction","date":"2022-09-20","arxiv_id":"2209.09481","n_code_links":1,"syntology":null},{"paper":null,"slug":"fovolnet-fast-volume-rendering-using-foveated","title":"FoVolNet: Fast Volume Rendering using Foveated Deep Neural Networks","date":"2022-09-20","arxiv_id":"2209.09965","n_code_links":0,"syntology":null},{"paper":null,"slug":"learning-acceptance-regions-for-many-classes","title":"Learning Acceptance Regions for Many Classes with Anomaly Detection","date":"2022-09-20","arxiv_id":"2209.09963","n_code_links":0,"syntology":null},{"paper":null,"slug":"robust-dynamic-state-estimation-of-multi","title":"Robust Dynamic State Estimation of Multi-Machine Power Networks with Solar Farms and Dynamics Loads","date":"2022-09-20","arxiv_id":"2209.10032","n_code_links":0,"syntology":null},{"paper":null,"slug":"superpixel-generation-and-clustering-for","title":"Deep Superpixel Generation and Clustering for Weakly Supervised Segmentation of Brain Tumors in MR Images","date":"2022-09-20","arxiv_id":"2209.09930","n_code_links":0,"syntology":null},{"paper":"/paper/vega-mt-the-jd-explore-academy-translation","slug":"vega-mt-the-jd-explore-academy-translation","title":"Vega-MT: The JD Explore Academy Translation System for WMT22","date":"2022-09-20","arxiv_id":"2209.09444","n_code_links":1,"syntology":null}],"record_sha256":"111082278e3ea8777044539b2a3a07a34f87563df3100674c34cc2d0517cb049","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}