{"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/39","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":39,"pages_in_order":65,"rows_per_page":100,"rows":[3801,3900],"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/38","next":"/method/test/papers/40","papers":[{"paper":null,"slug":"polynomial-optimization-enhancing-rlt","title":"Polynomial Optimization: Enhancing RLT relaxations with Conic Constraints","date":"2022-08-11","arxiv_id":"2208.05608","n_code_links":0,"syntology":null},{"paper":null,"slug":"robust-coordinated-longitudinal-control-of","title":"Robust Coordinated Longitudinal Control of MAV Based on Energy State","date":"2022-08-11","arxiv_id":"2208.05708","n_code_links":0,"syntology":null},{"paper":null,"slug":"shifted-windows-transformers-for-medical","title":"Shifted Windows Transformers for Medical Image Quality Assessment","date":"2022-08-11","arxiv_id":"2208.06034","n_code_links":0,"syntology":null},{"paper":"/paper/speech-enhancement-and-dereverberation-with","slug":"speech-enhancement-and-dereverberation-with","title":"Speech Enhancement and Dereverberation with Diffusion-based Generative Models","date":"2022-08-11","arxiv_id":"2208.05830","n_code_links":1,"syntology":null},{"paper":null,"slug":"structural-biases-for-improving-transformers-1","title":"Structural Biases for Improving Transformers on Translation into Morphologically Rich Languages","date":"2022-08-11","arxiv_id":"2208.06061","n_code_links":0,"syntology":null},{"paper":null,"slug":"top-gear-or-black-mirror-inferring-political","title":"Top Gear or Black Mirror: Inferring Political Leaning From Non-Political Content","date":"2022-08-11","arxiv_id":"2208.05662","n_code_links":0,"syntology":null},{"paper":null,"slug":"word-embeddings-distinguish-denominal-and","title":"Word-Embeddings Distinguish Denominal and Root-Derived Verbs in Semitic","date":"2022-08-11","arxiv_id":"2208.05721","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-data-driven-modular-architecture-with","title":"A data-driven modular architecture with denoising autoencoders for health indicator construction in a manufacturing process","date":"2022-08-10","arxiv_id":"2208.05208","n_code_links":0,"syntology":null},{"paper":"/paper/fedobd-opportunistic-block-dropout-for","slug":"fedobd-opportunistic-block-dropout-for","title":"FedOBD: Opportunistic Block Dropout for Efficiently Training Large-scale Neural Networks through Federated Learning","date":"2022-08-10","arxiv_id":"2208.05174","n_code_links":1,"syntology":null},{"paper":"/paper/looking-for-a-needle-in-a-haystack-a","slug":"looking-for-a-needle-in-a-haystack-a","title":"Looking for a Needle in a Haystack: A Comprehensive Study of Hallucinations in Neural Machine Translation","date":"2022-08-10","arxiv_id":"2208.05309","n_code_links":2,"syntology":null},{"paper":"/paper/non-contrastive-self-supervised-learning-of","slug":"non-contrastive-self-supervised-learning-of","title":"Non-Contrastive Self-Supervised Learning of Utterance-Level Speech Representations","date":"2022-08-10","arxiv_id":"2208.05413","n_code_links":1,"syntology":null},{"paper":"/paper/robust-continual-test-time-adaptation","slug":"robust-continual-test-time-adaptation","title":"NOTE: Robust Continual Test-time Adaptation Against Temporal Correlation","date":"2022-08-10","arxiv_id":"2208.05117","n_code_links":1,"syntology":{"ran":2,"of":3,"n_ran_checked":1,"n_instrument":1,"unverified":1,"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) · 1 unverified","official":{"repos":["taesikgong/note"],"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":["official"]}}},{"paper":"/paper/semantic-self-adaptation-enhancing","slug":"semantic-self-adaptation-enhancing","title":"Semantic Self-adaptation: Enhancing Generalization with a Single Sample","date":"2022-08-10","arxiv_id":"2208.05788","n_code_links":1,"syntology":null},{"paper":null,"slug":"testing-for-error-invariance-in-separable","title":"Testing for homogeneous treatment effects in linear and nonparametric instrumental variable models","date":"2022-08-10","arxiv_id":"2208.05344","n_code_links":0,"syntology":null},{"paper":"/paper/a-functional-connectivity-atlas-of-textit-c","slug":"a-functional-connectivity-atlas-of-textit-c","title":"Neural signal propagation atlas of C. elegans","date":"2022-08-09","arxiv_id":"2208.04790","n_code_links":1,"syntology":null},{"paper":null,"slug":"classification-of-electromagnetic","title":"Classification of electromagnetic interference induced image noise in an analog video link","date":"2022-08-09","arxiv_id":"2208.04614","n_code_links":0,"syntology":null},{"paper":"/paper/continual-prune-and-select-class-incremental","slug":"continual-prune-and-select-class-incremental","title":"Continual Prune-and-Select: Class-incremental learning with specialized subnetworks","date":"2022-08-09","arxiv_id":"2208.04952","n_code_links":1,"syntology":null},{"paper":null,"slug":"evaluation-of-a-beam-switching-smart-antenna","title":"Evaluation of a beam switching smart antenna array for use in traffic telematics V2X applications","date":"2022-08-09","arxiv_id":"2208.04858","n_code_links":0,"syntology":null},{"paper":"/paper/exploring-hate-speech-detection-with","slug":"exploring-hate-speech-detection-with","title":"Exploring Hate Speech Detection with HateXplain and BERT","date":"2022-08-09","arxiv_id":"2208.04489","n_code_links":1,"syntology":null},{"paper":null,"slug":"exploring-the-trade-off-between-human-driving","title":"Exploring the trade off between human driving imitation and safety for traffic simulation","date":"2022-08-09","arxiv_id":"2208.04803","n_code_links":0,"syntology":null},{"paper":null,"slug":"fisher-matrix-based-fault-detection-for-pmus","title":"Fisher Matrix Based Fault Detection for PMUs Data in Power Grids","date":"2022-08-09","arxiv_id":"2208.04637","n_code_links":0,"syntology":null},{"paper":null,"slug":"improving-covid-19-ct-classification-of-cnns","title":"Improving COVID-19 CT Classification of CNNs by Learning Parameter-Efficient Representation","date":"2022-08-09","arxiv_id":"2208.04718","n_code_links":0,"syntology":null},{"paper":null,"slug":"multi-task-fusion-via-reinforcement-learning","title":"Multi-Task Fusion via Reinforcement Learning for Long-Term User Satisfaction in Recommender Systems","date":"2022-08-09","arxiv_id":"2208.04560","n_code_links":0,"syntology":null},{"paper":"/paper/speaker-adaptive-lip-reading-with-user","slug":"speaker-adaptive-lip-reading-with-user","title":"Speaker-adaptive Lip Reading with User-dependent Padding","date":"2022-08-09","arxiv_id":"2208.04498","n_code_links":1,"syntology":null},{"paper":null,"slug":"continual-reinforcement-learning-with-tella","title":"Continual Reinforcement Learning with TELLA","date":"2022-08-08","arxiv_id":"2208.04287","n_code_links":0,"syntology":null},{"paper":"/paper/contrast-phys-unsupervised-video-based-remote","slug":"contrast-phys-unsupervised-video-based-remote","title":"Contrast-Phys: Unsupervised Video-based Remote Physiological Measurement via Spatiotemporal Contrast","date":"2022-08-08","arxiv_id":"2208.04378","n_code_links":1,"syntology":{"ran":1,"of":1,"n_ran_checked":1,"n_instrument":0,"unverified":0,"pointer_only":0,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","official":{"repos":["zhaodongsun/contrast-phys"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"deep-computational-model-for-the-inference-of","title":"Deep Computational Model for the Inference of Ventricular Activation Properties","date":"2022-08-08","arxiv_id":"2208.04028","n_code_links":0,"syntology":null},{"paper":null,"slug":"denoising-induction-motor-sounds-using-an","title":"Denoising Induction Motor Sounds Using an Autoencoder","date":"2022-08-08","arxiv_id":"2208.04462","n_code_links":0,"syntology":null},{"paper":null,"slug":"generalization-and-overfitting-in-matrix","title":"Generalization and Overfitting in Matrix Product State Machine Learning Architectures","date":"2022-08-08","arxiv_id":"2208.04372","n_code_links":0,"syntology":null},{"paper":"/paper/neural-architecture-search-as-multiobjective","slug":"neural-architecture-search-as-multiobjective","title":"Neural Architecture Search as Multiobjective Optimization Benchmarks: Problem Formulation and Performance Assessment","date":"2022-08-08","arxiv_id":"2208.04321","n_code_links":2,"syntology":null},{"paper":null,"slug":"a-machine-learning-approach-to-predict-the","title":"A machine learning approach to predict the structural and magnetic properties of Heusler alloy families","date":"2022-08-07","arxiv_id":"2208.12705","n_code_links":0,"syntology":null},{"paper":null,"slug":"an-example-of-use-of-variational-methods-in","title":"An example of use of Variational Methods in Quantum Machine Learning","date":"2022-08-07","arxiv_id":"2208.04316","n_code_links":0,"syntology":null},{"paper":null,"slug":"functional-characterizations-vs-finite-tests","title":"Finite Tests from Functional Characterizations","date":"2022-08-07","arxiv_id":"2208.03737","n_code_links":0,"syntology":null},{"paper":"/paper/granger-causality-using-neural-networks","slug":"granger-causality-using-neural-networks","title":"Granger Causality using Neural Networks","date":"2022-08-07","arxiv_id":"2208.03703","n_code_links":1,"syntology":null},{"paper":null,"slug":"generalizability-analysis-of-graph-based","title":"Generalizability Analysis of Graph-based Trajectory Predictor with Vectorized Representation","date":"2022-08-06","arxiv_id":"2208.03578","n_code_links":0,"syntology":null},{"paper":null,"slug":"triphlapan-predicting-hla-molecules-binding","title":"TripHLApan: predicting HLA molecules binding peptides based on triple coding matrix and transfer learning","date":"2022-08-06","arxiv_id":"2208.04314","n_code_links":0,"syntology":null},{"paper":"/paper/a-gaze-into-the-internal-logic-of-graph","slug":"a-gaze-into-the-internal-logic-of-graph","title":"A Gaze into the Internal Logic of Graph Neural Networks, with Logic","date":"2022-08-05","arxiv_id":"2208.03093","n_code_links":1,"syntology":null},{"paper":null,"slug":"a-lightweight-machine-learning-pipeline-for","title":"A Lightweight Machine Learning Pipeline for LiDAR-simulation","date":"2022-08-05","arxiv_id":"2208.03130","n_code_links":0,"syntology":null},{"paper":"/paper/a-self-interpretable-module-for-deep-image","slug":"a-self-interpretable-module-for-deep-image","title":"A self-interpretable module for deep image classification on small data","date":"2022-08-05","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":null,"slug":"a-sketch-is-worth-a-thousand-words-image","title":"A Sketch Is Worth a Thousand Words: Image Retrieval with Text and Sketch","date":"2022-08-05","arxiv_id":"2208.03354","n_code_links":0,"syntology":null},{"paper":null,"slug":"an-asp-framework-for-efficient-urban-traffic","title":"An ASP Framework for Efficient Urban Traffic Optimization","date":"2022-08-05","arxiv_id":"2208.03097","n_code_links":0,"syntology":null},{"paper":null,"slug":"construction-of-english-resume-corpus-and","title":"Construction of English Resume Corpus and Test with Pre-trained Language Models","date":"2022-08-05","arxiv_id":"2208.03219","n_code_links":0,"syntology":null},{"paper":"/paper/croloss-towards-a-customizable-loss-for","slug":"croloss-towards-a-customizable-loss-for","title":"CROLoss: Towards a Customizable Loss for Retrieval Models in Recommender Systems","date":"2022-08-05","arxiv_id":"2208.02971","n_code_links":1,"syntology":{"ran":1,"of":1,"n_ran_checked":1,"n_instrument":0,"unverified":0,"pointer_only":0,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","official":{"repos":["WDdeBWT/CROLoss"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":"/paper/hybrid-multimodal-feature-extraction-mining","slug":"hybrid-multimodal-feature-extraction-mining","title":"Hybrid Multimodal Feature Extraction, Mining and Fusion for Sentiment Analysis","date":"2022-08-05","arxiv_id":"2208.03051","n_code_links":1,"syntology":null},{"paper":null,"slug":"improving-task-generalization-via-unified","title":"Improving Task Generalization via Unified Schema Prompt","date":"2022-08-05","arxiv_id":"2208.03229","n_code_links":0,"syntology":null},{"paper":"/paper/knowledge-authoring-with-factual-english","slug":"knowledge-authoring-with-factual-english","title":"Knowledge Authoring with Factual English","date":"2022-08-05","arxiv_id":"2208.03094","n_code_links":1,"syntology":null},{"paper":null,"slug":"learning-from-data-in-the-mixed-adversarial","title":"Learning from data in the mixed adversarial non-adversarial case: Finding the helpers and ignoring the trolls","date":"2022-08-05","arxiv_id":"2208.03295","n_code_links":0,"syntology":null},{"paper":"/paper/towards-no-1-in-clue-semantic-matching","slug":"towards-no-1-in-clue-semantic-matching","title":"Towards No.1 in CLUE Semantic Matching Challenge: Pre-trained Language Model Erlangshen with Propensity-Corrected Loss","date":"2022-08-05","arxiv_id":"2208.02959","n_code_links":1,"syntology":null},{"paper":null,"slug":"a-review-of-machine-learning-and-algorithmic","title":"A Review of Machine Learning and Algorithmic Methods for Protein Phosphorylation Sites Prediction","date":"2022-08-04","arxiv_id":"2208.04311","n_code_links":0,"syntology":null},{"paper":null,"slug":"cfarnet-deep-learning-for-target-detection","title":"CFARnet: deep learning for target detection with constant false alarm rate","date":"2022-08-04","arxiv_id":"2208.02474","n_code_links":0,"syntology":null},{"paper":"/paper/cigan-a-python-package-for-handling-class","slug":"cigan-a-python-package-for-handling-class","title":"CIGAN: A Python Package for Handling Class Imbalance using Generative Adversarial Networks","date":"2022-08-04","arxiv_id":"2208.02931","n_code_links":1,"syntology":null},{"paper":"/paper/decision-sincnet-neurocognitive-models-of","slug":"decision-sincnet-neurocognitive-models-of","title":"Decision SincNet: Neurocognitive models of decision making that predict cognitive processes from neural signals","date":"2022-08-04","arxiv_id":"2208.02845","n_code_links":1,"syntology":null},{"paper":null,"slug":"deep-semi-supervised-and-self-supervised","title":"Deep Semi-Supervised and Self-Supervised Learning for Diabetic Retinopathy Detection","date":"2022-08-04","arxiv_id":"2208.02408","n_code_links":0,"syntology":null},{"paper":null,"slug":"feature-selection-with-gradient-descent-on","title":"Feature selection with gradient descent on two-layer networks in low-rotation regimes","date":"2022-08-04","arxiv_id":"2208.02789","n_code_links":0,"syntology":null},{"paper":"/paper/improved-post-hoc-probability-calibration-for","slug":"improved-post-hoc-probability-calibration-for","title":"Improved post-hoc probability calibration for out-of-domain MRI segmentation","date":"2022-08-04","arxiv_id":"2208.02870","n_code_links":1,"syntology":null},{"paper":null,"slug":"it-ist-ipleiria-response-to-the-call-for","title":"IT/IST/IPLeiria Response to the Call for Proposals on JPEG Pleno Point Cloud Coding","date":"2022-08-04","arxiv_id":"2208.02716","n_code_links":0,"syntology":null},{"paper":"/paper/memetic-algorithms-for-spatial-partitioning","slug":"memetic-algorithms-for-spatial-partitioning","title":"Memetic algorithms for Spatial Partitioning problems","date":"2022-08-04","arxiv_id":"2208.02867","n_code_links":1,"syntology":null},{"paper":null,"slug":"sa-net-v2-real-time-vehicle-detection-from","title":"SA-NET.v2: Real-time vehicle detection from oblique UAV images with use of uncertainty estimation in deep meta-learning","date":"2022-08-04","arxiv_id":"2208.04190","n_code_links":0,"syntology":null},{"paper":"/paper/towards-augmented-microscopy-with","slug":"towards-augmented-microscopy-with","title":"Towards Augmented Microscopy with Reinforcement Learning-Enhanced Workflows","date":"2022-08-04","arxiv_id":"2208.02865","n_code_links":1,"syntology":null},{"paper":"/paper/visually-evaluating-generative-adversarial","slug":"visually-evaluating-generative-adversarial","title":"Visually Evaluating Generative Adversarial Networks Using Itself under Multivariate Time Series","date":"2022-08-04","arxiv_id":"2208.02649","n_code_links":1,"syntology":null},{"paper":null,"slug":"a-deep-learning-approach-to-detect-lean","title":"A Deep Learning Approach to Detect Lean Blowout in Combustion Systems","date":"2022-08-03","arxiv_id":"2208.01871","n_code_links":0,"syntology":null},{"paper":"/paper/a-feature-space-multimodal-data-augmentation","slug":"a-feature-space-multimodal-data-augmentation","title":"A Feature-space Multimodal Data Augmentation Technique for Text-video Retrieval","date":"2022-08-03","arxiv_id":"2208.02080","n_code_links":1,"syntology":null},{"paper":null,"slug":"adaptive-domain-generalization-via-online","title":"Adaptive Domain Generalization via Online Disagreement Minimization","date":"2022-08-03","arxiv_id":"2208.01996","n_code_links":0,"syntology":null},{"paper":"/paper/automatic-speech-recognition-in-german-a","slug":"automatic-speech-recognition-in-german-a","title":"Automatic Speech Recognition in German: A Detailed Error Analysis","date":"2022-08-03","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"equivariant-disentangled-transformation-for","title":"Equivariant Disentangled Transformation for Domain Generalization under Combination Shift","date":"2022-08-03","arxiv_id":"2208.02011","n_code_links":0,"syntology":null},{"paper":"/paper/segmented-learning-for-class-of-service","slug":"segmented-learning-for-class-of-service","title":"Segmented Learning for Class-of-Service Network Traffic Classification","date":"2022-08-03","arxiv_id":"2208.01793","n_code_links":1,"syntology":null},{"paper":null,"slug":"weak-instruments-first-stage","title":"Weak Instruments, First-Stage Heteroskedasticity, the Robust F-Test and a GMM Estimator with the Weight Matrix Based on First-Stage Residuals","date":"2022-08-03","arxiv_id":"2208.01967","n_code_links":0,"syntology":null},{"paper":"/paper/connection-reduction-is-all-you-need","slug":"connection-reduction-is-all-you-need","title":"Connection Reduction of DenseNet for Image Recognition","date":"2022-08-02","arxiv_id":"2208.01424","n_code_links":1,"syntology":null},{"paper":null,"slug":"data-driven-fast-frequency-control-using","title":"Data-Driven Fast Frequency Control using Inverter-Based Resources","date":"2022-08-02","arxiv_id":"2208.01761","n_code_links":0,"syntology":null},{"paper":null,"slug":"doubly-robust-estimation-of-local-average","title":"Doubly Robust Estimation of Local Average Treatment Effects Using Inverse Probability Weighted Regression Adjustment","date":"2022-08-02","arxiv_id":"2208.01300","n_code_links":0,"syntology":null},{"paper":"/paper/in-hand-pose-estimation-and-pin-inspection","slug":"in-hand-pose-estimation-and-pin-inspection","title":"In-Hand Pose Estimation and Pin Inspection for Insertion of Through-Hole Components","date":"2022-08-02","arxiv_id":"2208.01284","n_code_links":1,"syntology":null},{"paper":null,"slug":"joint-learning-based-causal-relation","title":"Joint Learning-based Causal Relation Extraction from Biomedical Literature","date":"2022-08-02","arxiv_id":"2208.01316","n_code_links":0,"syntology":null},{"paper":null,"slug":"mates2motion-learning-how-mechanical-cad","title":"Mates2Motion: Learning How Mechanical CAD Assemblies Work","date":"2022-08-02","arxiv_id":"2208.01779","n_code_links":0,"syntology":null},{"paper":"/paper/memo-coverage-guided-model-generation-for","slug":"memo-coverage-guided-model-generation-for","title":"COMET: Coverage-guided Model Generation For Deep Learning Library Testing","date":"2022-08-02","arxiv_id":"2208.01508","n_code_links":1,"syntology":null},{"paper":null,"slug":"recognizing-and-extracting-cybersecurtity","title":"Recognizing and Extracting Cybersecurtity-relevant Entities from Text","date":"2022-08-02","arxiv_id":"2208.01693","n_code_links":0,"syntology":null},{"paper":null,"slug":"self-supervised-traversability-prediction-by","title":"Self-Supervised Traversability Prediction by Learning to Reconstruct Safe Terrain","date":"2022-08-02","arxiv_id":"2208.01329","n_code_links":0,"syntology":null},{"paper":null,"slug":"signature-based-validation-of-real-world","title":"Signature-based validation of real-world economic scenarios","date":"2022-08-02","arxiv_id":"2208.07251","n_code_links":0,"syntology":null},{"paper":"/paper/viskositas-viscosity-prediction-of","slug":"viskositas-viscosity-prediction-of","title":"Viskositas: Viscosity Prediction of Multicomponent Chemical Systems","date":"2022-08-02","arxiv_id":"2208.01440","n_code_links":1,"syntology":null},{"paper":"/paper/a-knee-cannot-have-lung-disease-out-of","slug":"a-knee-cannot-have-lung-disease-out-of","title":"A knee cannot have lung disease: out-of-distribution detection with in-distribution voting using the medical example of chest X-ray classification","date":"2022-08-01","arxiv_id":"2208.01077","n_code_links":1,"syntology":null},{"paper":"/paper/disparate-censorship-undertesting-a-source-of","slug":"disparate-censorship-undertesting-a-source-of","title":"Disparate Censorship & Undertesting: A Source of Label Bias in Clinical Machine Learning","date":"2022-08-01","arxiv_id":"2208.01127","n_code_links":1,"syntology":null},{"paper":null,"slug":"dynamic-batch-adaptation","title":"Dynamic Batch Adaptation","date":"2022-08-01","arxiv_id":"2208.00815","n_code_links":0,"syntology":null},{"paper":null,"slug":"eboca-evidences-for-biomedical-concepts","title":"EBOCA: Evidences for BiOmedical Concepts Association Ontology","date":"2022-08-01","arxiv_id":"2208.01093","n_code_links":0,"syntology":null},{"paper":"/paper/few-shot-adaptation-works-with-unpredictable","slug":"few-shot-adaptation-works-with-unpredictable","title":"Few-shot Adaptation Works with UnpredicTable Data","date":"2022-08-01","arxiv_id":"2208.01009","n_code_links":1,"syntology":null},{"paper":"/paper/improving-the-trainability-of-deep-neural","slug":"improving-the-trainability-of-deep-neural","title":"Improving the Trainability of Deep Neural Networks through Layerwise Batch-Entropy Regularization","date":"2022-08-01","arxiv_id":"2208.01134","n_code_links":2,"syntology":null},{"paper":null,"slug":"interpretable-time-series-clustering-using","title":"Interpretable Time Series Clustering Using Local Explanations","date":"2022-08-01","arxiv_id":"2208.01152","n_code_links":0,"syntology":null},{"paper":null,"slug":"samplematch-drum-sample-retrieval-by-musical","title":"SampleMatch: Drum Sample Retrieval by Musical Context","date":"2022-08-01","arxiv_id":"2208.01141","n_code_links":0,"syntology":null},{"paper":"/paper/textworldexpress-simulating-text-games-at-one","slug":"textworldexpress-simulating-text-games-at-one","title":"TextWorldExpress: Simulating Text Games at One Million Steps Per Second","date":"2022-08-01","arxiv_id":"2208.01174","n_code_links":2,"syntology":null},{"paper":"/paper/unifying-approaches-in-data-subset-selection","slug":"unifying-approaches-in-data-subset-selection","title":"Unifying Approaches in Active Learning and Active Sampling via Fisher Information and Information-Theoretic Quantities","date":"2022-08-01","arxiv_id":"2208.00549","n_code_links":1,"syntology":null},{"paper":"/paper/chinese-grammatical-error-correction-based-on-1","slug":"chinese-grammatical-error-correction-based-on-1","title":"Chinese grammatical error correction based on knowledge distillation","date":"2022-07-31","arxiv_id":"2208.00351","n_code_links":2,"syntology":null},{"paper":"/paper/descod-ecg-deep-score-based-diffusion-model","slug":"descod-ecg-deep-score-based-diffusion-model","title":"DeScoD-ECG: Deep Score-Based Diffusion Model for ECG Baseline Wander and Noise Removal","date":"2022-07-31","arxiv_id":"2208.00542","n_code_links":1,"syntology":null},{"paper":"/paper/feather-light-fourier-domain-adaptation-in","slug":"feather-light-fourier-domain-adaptation-in","title":"Feather-Light Fourier Domain Adaptation in Magnetic Resonance Imaging","date":"2022-07-31","arxiv_id":"2208.00474","n_code_links":1,"syntology":null},{"paper":"/paper/mismatching-aware-unsupervised-translation","slug":"mismatching-aware-unsupervised-translation","title":"Mismatching-Aware Unsupervised Translation Quality Estimation For Low-Resource Languages","date":"2022-07-31","arxiv_id":"2208.00463","n_code_links":1,"syntology":null},{"paper":null,"slug":"pasta-a-dataset-for-modeling-participant","title":"PASTA: A Dataset for Modeling Participant States in Narratives","date":"2022-07-31","arxiv_id":"2208.00329","n_code_links":0,"syntology":null},{"paper":null,"slug":"towards-intercultural-affect-recognition","title":"Towards Intercultural Affect Recognition: Audio-Visual Affect Recognition in the Wild Across Six Cultures","date":"2022-07-31","arxiv_id":"2208.00344","n_code_links":0,"syntology":null},{"paper":"/paper/vector-based-data-improves-left-right-eye","slug":"vector-based-data-improves-left-right-eye","title":"Vector-Based Data Improves Left-Right Eye-Tracking Classifier Performance After a Covariate Distributional Shift","date":"2022-07-31","arxiv_id":"2208.00465","n_code_links":1,"syntology":null},{"paper":"/paper/resolution-enhancement-of-placenta","slug":"resolution-enhancement-of-placenta","title":"Resolution enhancement of placenta histological images using deep learning","date":"2022-07-30","arxiv_id":"2208.00163","n_code_links":1,"syntology":null},{"paper":null,"slug":"a-comparison-study-of-the-detection-limit-of","title":"A Comparison Study of the Detection Limit of Omicron SARS-CoV-2 Nucleocapsid by various Rapid Antigen Tests","date":"2022-07-29","arxiv_id":"2208.04236","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-review-of-deep-learning-techniques-for-1","title":"A review of Deep learning Techniques for COVID-19 identification on Chest CT images","date":"2022-07-29","arxiv_id":"2208.00032","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-transfer-learning-based-approach-to-marine","title":"A Transfer Learning-Based Approach to Marine Vessel Re-Identification","date":"2022-07-29","arxiv_id":"2207.14500","n_code_links":0,"syntology":null},{"paper":null,"slug":"alphavc-high-performance-and-efficient","title":"AlphaVC: High-Performance and Efficient Learned Video Compression","date":"2022-07-29","arxiv_id":"2207.14678","n_code_links":0,"syntology":null}],"record_sha256":"f7a380c9a0fe7b50673ffe6660863dd39c3a057cd90d60c82b5ea62d7c76c334","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}