{"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/prediction/papers/55","list_of":"/task/prediction","task":"Prediction","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":55,"pages_in_order":88,"rows_per_page":100,"rows":[5401,5500],"of":8760,"counts":{"archive_papers_tagged":8760,"with_a_code_link":2835,"where_syntology_ran_a_sample":607,"not_listed_spam_title":0,"listed":8760,"listed_where_code_ran":607,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":519,"every_run_a_failure_of_syntologys_instrument":88,"listed_with_a_run_with_no_instrument_failure":519,"listed_every_run_a_failure_of_syntologys_instrument":88,"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/prediction","prev":"/task/prediction/papers/54","next":"/task/prediction/papers/56","papers":[{"url":null,"slug":"aging-prediction-using-deep-generative-model","title":"Aging prediction using deep generative model toward the development of preventive medicine","date":"2022-08-23","arxiv_id":"2208.10797","repositories_listed":0,"syntology":null},{"url":null,"slug":"link-prediction-with-continuous-time","title":"Link prediction with continuous-time classical and quantum walks","date":"2022-08-23","arxiv_id":"2208.11030","repositories_listed":0,"syntology":null},{"url":null,"slug":"quality-constant-per-shot-encoding-by-two","title":"Quality-Constant Per-Shot Encoding by Two-Pass Learning-based Rate Factor Prediction","date":"2022-08-23","arxiv_id":"2208.10739","repositories_listed":0,"syntology":null},{"url":null,"slug":"atrial-fibrillation-recurrence-risk","title":"Atrial Fibrillation Recurrence Risk Prediction from 12-lead ECG Recorded Pre- and Post-Ablation Procedure","date":"2022-08-22","arxiv_id":"2208.10550","repositories_listed":0,"syntology":null},{"url":null,"slug":"dider-discovering-interpretable-dynamically","title":"DIDER: Discovering Interpretable Dynamically Evolving Relations","date":"2022-08-22","arxiv_id":"2208.10592","repositories_listed":0,"syntology":null},{"url":null,"slug":"hierarchical-capsule-prediction-network-for","title":"Hierarchical Capsule Prediction Network for Marketing Campaigns Effect","date":"2022-08-22","arxiv_id":"2208.10113","repositories_listed":0,"syntology":null},{"url":null,"slug":"metarf-differentiable-random-forest-for","title":"MetaRF: Differentiable Random Forest for Reaction Yield Prediction with a Few Trails","date":"2022-08-22","arxiv_id":"2208.10083","repositories_listed":0,"syntology":null},{"url":null,"slug":"alexa-predict-my-flight-delay","title":"Alexa, Predict My Flight Delay","date":"2022-08-21","arxiv_id":"2208.09921","repositories_listed":0,"syntology":null},{"url":null,"slug":"are-you-comfortable-now-deep-learning-the","title":"Are You Comfortable Now: Deep Learning the Temporal Variation in Thermal Comfort in Winters","date":"2022-08-20","arxiv_id":"2208.09628","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-to-predict-test-effectiveness","title":"Learning to predict test effectiveness","date":"2022-08-20","arxiv_id":"2208.09623","repositories_listed":0,"syntology":null},{"url":null,"slug":"feature-selection-for-fault-detection-and","title":"Feature Selection for Fault Detection and Prediction based on Event Log Analysis","date":"2022-08-19","arxiv_id":"2208.09440","repositories_listed":0,"syntology":null},{"url":null,"slug":"pixel-wise-prediction-based-visual-odometry","title":"Pixel-Wise Prediction based Visual Odometry via Uncertainty Estimation","date":"2022-08-18","arxiv_id":"2208.08892","repositories_listed":0,"syntology":null},{"url":null,"slug":"lama-net-unsupervised-domain-adaptation-via","title":"LAMA-Net: Unsupervised Domain Adaptation via Latent Alignment and Manifold Learning for RUL Prediction","date":"2022-08-17","arxiv_id":"2208.08388","repositories_listed":0,"syntology":null},{"url":"/paper/transformer-based-deep-learning-model-for","slug":"transformer-based-deep-learning-model-for","title":"Transformer-Based Deep Learning Model for Stock Price Prediction: A Case Study on Bangladesh Stock Market","date":"2022-08-17","arxiv_id":"2208.08300","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-convolutional-surrogates-and-degrees-of","title":"Deep convolutional surrogates and degrees of freedom in thermal design","date":"2022-08-16","arxiv_id":"2208.07482","repositories_listed":0,"syntology":null},{"url":null,"slug":"prediction-of-seismic-intensity-distributions","title":"Prediction of Seismic Intensity Distributions Using Neural Networks","date":"2022-08-16","arxiv_id":"2208.07565","repositories_listed":0,"syntology":null},{"url":null,"slug":"dueta-traffic-congestion-propagation-pattern","title":"DuETA: Traffic Congestion Propagation Pattern Modeling via Efficient Graph Learning for ETA Prediction at Baidu Maps","date":"2022-08-15","arxiv_id":"2208.06979","repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-modal-transformer-path-prediction-for","title":"Multi-modal Transformer Path Prediction for Autonomous Vehicle","date":"2022-08-15","arxiv_id":"2208.07256","repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-spatio-temporal-cross-platform-graph","title":"Towards Spatio-Temporal Cross-Platform Graph Embedding Fusion for Urban Traffic Flow Prediction","date":"2022-08-15","arxiv_id":"2208.06947","repositories_listed":0,"syntology":null},{"url":null,"slug":"watchped-pedestrian-crossing-intention","title":"WatchPed: Pedestrian Crossing Intention Prediction Using Embedded Sensors of Smartwatch","date":"2022-08-15","arxiv_id":"2208.07441","repositories_listed":0,"syntology":null},{"url":null,"slug":"b-eta-divergence-based-latent-factorization","title":"\\b{eta}-Divergence-Based Latent Factorization of Tensors model for QoS prediction","date":"2022-08-14","arxiv_id":"2208.06778","repositories_listed":0,"syntology":null},{"url":null,"slug":"gedi-a-graph-based-end-to-end-data-imputation","title":"GEDI: A Graph-based End-to-end Data Imputation Framework","date":"2022-08-13","arxiv_id":"2208.06573","repositories_listed":0,"syntology":null},{"url":null,"slug":"continual-transfer-learning-for-cross-domain","title":"Continual Transfer Learning for Cross-Domain Click-Through Rate Prediction at Taobao","date":"2022-08-11","arxiv_id":"2208.05728","repositories_listed":0,"syntology":null},{"url":null,"slug":"real-time-massive-mimo-channel-prediction-a","title":"Real-Time Massive MIMO Channel Prediction: A Combination of Deep Learning and NeuralProphet","date":"2022-08-11","arxiv_id":"2208.05607","repositories_listed":0,"syntology":null},{"url":null,"slug":"dual-domain-adversarial-learning-for-audio","title":"Dual Domain-Adversarial Learning for Audio-Visual Saliency Prediction","date":"2022-08-10","arxiv_id":"2208.05220","repositories_listed":0,"syntology":null},{"url":null,"slug":"evolvehypergraph-group-aware-dynamic","title":"EvolveHypergraph: Group-Aware Dynamic Relational Reasoning for Trajectory Prediction","date":"2022-08-10","arxiv_id":"2208.05470","repositories_listed":0,"syntology":null},{"url":null,"slug":"explainable-prediction-of-qcodes-for-notams","title":"Explainable prediction of Qcodes for NOTAMs using column generation","date":"2022-08-09","arxiv_id":"2208.04955","repositories_listed":0,"syntology":null},{"url":null,"slug":"privacy-aware-adversarial-network-in-human","title":"Privacy-Aware Adversarial Network in Human Mobility Prediction","date":"2022-08-09","arxiv_id":"2208.05009","repositories_listed":0,"syntology":null},{"url":"/paper/tsrformer-table-structure-recognition-with","slug":"tsrformer-table-structure-recognition-with","title":"TSRFormer: Table Structure Recognition with Transformers","date":"2022-08-09","arxiv_id":"2208.04921","repositories_listed":0,"syntology":null},{"url":null,"slug":"unsupervised-question-clarity-prediction","title":"Unsupervised Question Clarity Prediction Through Retrieved Item Coherency","date":"2022-08-09","arxiv_id":"2208.04882","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-to-learn-to-predict-performance","title":"Learning to Learn to Predict Performance Regressions in Production at Meta","date":"2022-08-08","arxiv_id":"2208.04351","repositories_listed":0,"syntology":null},{"url":null,"slug":"liquid-state-machine-empowered-reflection","title":"Liquid State Machine-Empowered Reflection Tracking in RIS-Aided THz Communications","date":"2022-08-08","arxiv_id":"2208.04400","repositories_listed":0,"syntology":null},{"url":null,"slug":"bias-reducing-multitask-learning-on-mental","title":"Bias Reducing Multitask Learning on Mental Health Prediction","date":"2022-08-07","arxiv_id":"2208.03621","repositories_listed":0,"syntology":null},{"url":null,"slug":"optimal-tracking-in-prediction-with-expert","title":"Optimal Tracking in Prediction with Expert Advice","date":"2022-08-07","arxiv_id":"2208.03708","repositories_listed":0,"syntology":null},{"url":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","repositories_listed":0,"syntology":null},{"url":null,"slug":"short-duration-traffic-flow-prediction-using","title":"Short Duration Traffic Flow Prediction Using Kalman Filtering","date":"2022-08-06","arxiv_id":"2208.03415","repositories_listed":0,"syntology":null},{"url":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","repositories_listed":0,"syntology":null},{"url":null,"slug":"isoform-function-prediction-using-deep-neural","title":"Isoform Function Prediction Using a Deep Neural Network","date":"2022-08-05","arxiv_id":"2208.03325","repositories_listed":0,"syntology":null},{"url":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","repositories_listed":0,"syntology":null},{"url":null,"slug":"research-modeling-price-elasticity-for","title":"Modeling Price Elasticity for Occupancy Prediction in Hotel Dynamic Pricing","date":"2022-08-04","arxiv_id":"2208.03135","repositories_listed":0,"syntology":null},{"url":null,"slug":"unsupervised-graph-spectral-feature-denoising","title":"Unsupervised Graph Spectral Feature Denoising for Crop Yield Prediction","date":"2022-08-04","arxiv_id":"2208.02714","repositories_listed":0,"syntology":null},{"url":null,"slug":"empirical-study-of-overfitting-in-deep-fnn","title":"Empirical Study of Overfitting in Deep FNN Prediction Models for Breast Cancer Metastasis","date":"2022-08-03","arxiv_id":"2208.02150","repositories_listed":0,"syntology":null},{"url":null,"slug":"link-prediction-on-heterophilic-graphs-via","title":"Link Prediction on Heterophilic Graphs via Disentangled Representation Learning","date":"2022-08-03","arxiv_id":"2208.01820","repositories_listed":0,"syntology":null},{"url":null,"slug":"compound-density-networks-for-risk-prediction","title":"Compound Density Networks for Risk Prediction using Electronic Health Records","date":"2022-08-02","arxiv_id":"2208.01320","repositories_listed":0,"syntology":null},{"url":null,"slug":"flood-prediction-using-machine-learning-1","title":"Flood Prediction Using Machine Learning Models","date":"2022-08-02","arxiv_id":"2208.01234","repositories_listed":0,"syntology":null},{"url":null,"slug":"overlooked-poses-actually-make-sense","title":"Overlooked Poses Actually Make Sense: Distilling Privileged Knowledge for Human Motion Prediction","date":"2022-08-02","arxiv_id":"2208.01302","repositories_listed":0,"syntology":null},{"url":null,"slug":"exploring-the-glide-model-for-human-action","title":"Exploring the GLIDE model for Human Action-effect Prediction","date":"2022-08-01","arxiv_id":"2208.01136","repositories_listed":0,"syntology":null},{"url":null,"slug":"sampling-communication-and-prediction-co","title":"Sampling, Communication, and Prediction Co-Design for Synchronizing the Real-World Device and Digital Model in Metaverse","date":"2022-07-31","arxiv_id":"2208.04233","repositories_listed":0,"syntology":null},{"url":null,"slug":"robust-trajectory-prediction-against","title":"Robust Trajectory Prediction against Adversarial Attacks","date":"2022-07-29","arxiv_id":"2208.00094","repositories_listed":0,"syntology":null},{"url":null,"slug":"entity-type-prediction-leveraging-graph-walks","title":"Entity Type Prediction Leveraging Graph Walks and Entity Descriptions","date":"2022-07-28","arxiv_id":"2207.14094","repositories_listed":0,"syntology":null},{"url":null,"slug":"lad-language-models-as-data-for-zero-shot","title":"LAD: Language Models as Data for Zero-Shot Dialog","date":"2022-07-28","arxiv_id":"2207.14393","repositories_listed":0,"syntology":null},{"url":null,"slug":"re-thinking-and-re-labeling-lidc-idri-for","title":"Re-thinking and Re-labeling LIDC-IDRI for Robust Pulmonary Cancer Prediction","date":"2022-07-28","arxiv_id":"2207.14238","repositories_listed":0,"syntology":null},{"url":null,"slug":"conformal-prediction-bands-for-two","title":"Conformal Prediction Bands for Two-Dimensional Functional Time Series","date":"2022-07-27","arxiv_id":"2207.13656","repositories_listed":0,"syntology":null},{"url":null,"slug":"iot-based-smart-water-quality-prediction-for","title":"IoT based Smart Water Quality Prediction for Biofloc Aquaculture","date":"2022-07-27","arxiv_id":"2208.08866","repositories_listed":0,"syntology":null},{"url":null,"slug":"label-only-membership-inference-attack","title":"Label-Only Membership Inference Attack against Node-Level Graph Neural Networks","date":"2022-07-27","arxiv_id":"2207.13766","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-data-driven-method-for-multi-step","title":"A Data Driven Method for Multi-step Prediction of Ship Roll Motion in High Sea States","date":"2022-07-26","arxiv_id":"2207.12673","repositories_listed":0,"syntology":null},{"url":null,"slug":"gcn-wp-semi-supervised-graph-convolutional","title":"GCN-WP -- Semi-Supervised Graph Convolutional Networks for Win Prediction in Esports","date":"2022-07-26","arxiv_id":"2207.13191","repositories_listed":0,"syntology":null},{"url":null,"slug":"modeling-the-social-influence-of-covid-19-via","title":"Modeling the Social Influence of COVID-19 via Personalized Propagation with Deep Learning","date":"2022-07-26","arxiv_id":"2207.13016","repositories_listed":0,"syntology":null},{"url":null,"slug":"graph-neural-networks-for-the-prediction-of-1","title":"Graph neural networks for the prediction of molecular structure-property relationships","date":"2022-07-25","arxiv_id":"2208.04852","repositories_listed":0,"syntology":null},{"url":null,"slug":"data-driven-models-to-anticipate-critical","title":"Data-driven Models to Anticipate Critical Voltage Events in Power Systems","date":"2022-07-24","arxiv_id":"2207.11803","repositories_listed":0,"syntology":null},{"url":null,"slug":"prediction-intervals-in-the-beta","title":"Prediction Intervals in the Beta Autoregressive Moving Average Model","date":"2022-07-24","arxiv_id":"2207.11628","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-transferable-intersection-reconstruction","title":"A Transferable Intersection Reconstruction Network for Traffic Speed Prediction","date":"2022-07-22","arxiv_id":"2207.11030","repositories_listed":0,"syntology":null},{"url":null,"slug":"uncertainty-aware-multi-modal-learning-via","title":"Uncertainty-aware Multi-modal Learning via Cross-modal Random Network Prediction","date":"2022-07-22","arxiv_id":"2207.10851","repositories_listed":0,"syntology":null},{"url":null,"slug":"ensemble-learning-for-efficient-vvc-bitrate","title":"Ensemble Learning for Efficient VVC Bitrate Ladder Prediction","date":"2022-07-21","arxiv_id":"2207.10317","repositories_listed":0,"syntology":null},{"url":null,"slug":"heterogeneous-ensemble-learning-for-enhanced","title":"Heterogeneous Ensemble Learning for Enhanced Crash Forecasts -- A Frequentest and Machine Learning based Stacking Framework","date":"2022-07-21","arxiv_id":"2207.10721","repositories_listed":0,"syntology":null},{"url":null,"slug":"aware-of-the-history-trajectory-forecasting","title":"Aware of the History: Trajectory Forecasting with the Local Behavior Data","date":"2022-07-20","arxiv_id":"2207.09646","repositories_listed":0,"syntology":null},{"url":null,"slug":"era-expert-retrieval-and-assembly-for-early","title":"ERA: Expert Retrieval and Assembly for Early Action Prediction","date":"2022-07-20","arxiv_id":"2207.09675","repositories_listed":0,"syntology":null},{"url":null,"slug":"spatio-temporal-prediction-in-video-coding-by-1","title":"Spatio-temporal prediction in video coding by non-local means refined motion compensation","date":"2022-07-20","arxiv_id":"2207.09729","repositories_listed":0,"syntology":null},{"url":null,"slug":"spatio-temporal-prediction-in-video-coding-by-2","title":"Spatio-temporal prediction in video coding by best approximation","date":"2022-07-20","arxiv_id":"2207.09727","repositories_listed":0,"syntology":null},{"url":null,"slug":"rclane-relay-chain-prediction-for-lane","title":"RCLane: Relay Chain Prediction for Lane Detection","date":"2022-07-19","arxiv_id":"2207.09399","repositories_listed":0,"syntology":null},{"url":null,"slug":"action-based-contrastive-learning-for","title":"Action-based Contrastive Learning for Trajectory Prediction","date":"2022-07-18","arxiv_id":"2207.08664","repositories_listed":0,"syntology":null},{"url":null,"slug":"data-driven-self-triggered-control-via","title":"Data-driven Self-triggered Control via Trajectory Prediction","date":"2022-07-18","arxiv_id":"2207.08596","repositories_listed":0,"syntology":null},{"url":null,"slug":"online-prediction-in-sub-linear-space","title":"Online Prediction in Sub-linear Space","date":"2022-07-16","arxiv_id":"2207.07974","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-approach-for-link-prediction-in-directed","title":"An Approach for Link Prediction in Directed Complex Networks based on Asymmetric Similarity-Popularity","date":"2022-07-15","arxiv_id":"2207.07399","repositories_listed":0,"syntology":null},{"url":null,"slug":"coronavirus-disease-situation-analysis-and","title":"Coronavirus disease situation analysis and prediction using machine learning: a study on Bangladeshi population","date":"2022-07-12","arxiv_id":"2207.13056","repositories_listed":0,"syntology":null},{"url":null,"slug":"ddi-prediction-via-heterogeneous-graph","title":"DDI Prediction via Heterogeneous Graph Attention Networks","date":"2022-07-12","arxiv_id":"2207.05672","repositories_listed":0,"syntology":null},{"url":null,"slug":"exploiting-social-graph-networks-for-emotion","title":"Exploiting Social Graph Networks for Emotion Prediction","date":"2022-07-12","arxiv_id":"2207.05820","repositories_listed":0,"syntology":null},{"url":null,"slug":"the-untold-impact-of-learning-approaches-on","title":"The Untold Impact of Learning Approaches on Software Fault-Proneness Predictions","date":"2022-07-12","arxiv_id":"2207.05710","repositories_listed":0,"syntology":null},{"url":null,"slug":"few-shot-semantic-relation-prediction-across","title":"Few-Shot Semantic Relation Prediction across Heterogeneous Graphs","date":"2022-07-11","arxiv_id":"2207.05068","repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-task-envisioning-transformer-based","title":"Multi-task Envisioning Transformer-based Autoencoder for Corporate Credit Rating Migration Early Prediction","date":"2022-07-10","arxiv_id":"2207.04539","repositories_listed":0,"syntology":null},{"url":null,"slug":"cocatt-a-cognitive-conditioned-driver-1","title":"CoCAtt: A Cognitive-Conditioned Driver Attention Dataset (Supplementary Material)","date":"2022-07-08","arxiv_id":"2207.04028","repositories_listed":0,"syntology":null},{"url":null,"slug":"mobile-mimo-channel-prediction-with-ode-rnn-a","title":"Mobile MIMO Channel Prediction with ODE-RNN: a Physics-Inspired Adaptive Approach","date":"2022-07-08","arxiv_id":"2207.03736","repositories_listed":0,"syntology":null},{"url":null,"slug":"predicting-li-ion-battery-cycle-life-with","title":"Predicting Li-ion Battery Cycle Life with LSTM RNN","date":"2022-07-08","arxiv_id":"2207.03687","repositories_listed":0,"syntology":null},{"url":null,"slug":"spatio-temporal-prediction-in-video-coding-by","title":"Spatio-temporal prediction in video coding by spatially refined motion compensation","date":"2022-07-08","arxiv_id":"2207.03766","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-survey-on-hyperlink-prediction","title":"A Survey on Hyperlink Prediction","date":"2022-07-06","arxiv_id":"2207.02911","repositories_listed":0,"syntology":null},{"url":null,"slug":"improved-conformalized-quantile-regression","title":"Improved conformalized quantile regression","date":"2022-07-06","arxiv_id":"2207.02808","repositories_listed":0,"syntology":null},{"url":null,"slug":"pac-prediction-sets-for-meta-learning","title":"PAC Prediction Sets for Meta-Learning","date":"2022-07-06","arxiv_id":"2207.02440","repositories_listed":0,"syntology":null},{"url":null,"slug":"pre-training-transformers-for-molecular","title":"Pre-training Transformers for Molecular Property Prediction Using Reaction Prediction","date":"2022-07-06","arxiv_id":"2207.02724","repositories_listed":0,"syntology":null},{"url":"/paper/self-constrained-inference-optimization-on","slug":"self-constrained-inference-optimization-on","title":"Self-Constrained Inference Optimization on Structural Groups for Human Pose Estimation","date":"2022-07-06","arxiv_id":"2207.02425","repositories_listed":0,"syntology":null},{"url":null,"slug":"white-matter-tracts-are-point-clouds","title":"White Matter Tracts are Point Clouds: Neuropsychological Score Prediction and Critical Region Localization via Geometric Deep Learning","date":"2022-07-06","arxiv_id":"2207.02402","repositories_listed":0,"syntology":null},{"url":null,"slug":"clustered-saliency-prediction","title":"Clustered Saliency Prediction","date":"2022-07-05","arxiv_id":"2207.02205","repositories_listed":0,"syntology":null},{"url":null,"slug":"scoring-rules-for-performative-binary","title":"Scoring Rules for Performative Binary Prediction","date":"2022-07-05","arxiv_id":"2207.02847","repositories_listed":0,"syntology":null},{"url":null,"slug":"assessing-the-performance-of-automated","title":"Assessing the Performance of Automated Prediction and Ranking of Patient Age from Chest X-rays Against Clinicians","date":"2022-07-04","arxiv_id":"2207.01302","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-disentangled-representations-for-4","title":"Learning Disentangled Representations for Controllable Human Motion Prediction","date":"2022-07-04","arxiv_id":"2207.01388","repositories_listed":0,"syntology":null},{"url":null,"slug":"masked-self-supervision-for-remaining-useful","title":"Masked Self-Supervision for Remaining Useful Lifetime Prediction in Machine Tools","date":"2022-07-04","arxiv_id":"2207.01219","repositories_listed":0,"syntology":null},{"url":null,"slug":"multiple-selection-approximation-for-improved","title":"Multiple Selection Approximation for Improved Spatio-Temporal Prediction in Video Coding","date":"2022-07-04","arxiv_id":"2207.01207","repositories_listed":0,"syntology":null},{"url":null,"slug":"nodetrans-a-graph-transfer-learning-approach","title":"NodeTrans: A Graph Transfer Learning Approach for Traffic Prediction","date":"2022-07-04","arxiv_id":"2207.01301","repositories_listed":0,"syntology":null},{"url":null,"slug":"reusing-the-h-264-avc-deblocking-filter-for","title":"Reusing the H.264/AVC deblocking filter for efficient spatio-temporal prediction in video coding","date":"2022-07-04","arxiv_id":"2207.01210","repositories_listed":0,"syntology":null},{"url":null,"slug":"vehicle-trajectory-prediction-on-highways","title":"Vehicle Trajectory Prediction on Highways Using Bird Eye View Representations and Deep Learning","date":"2022-07-04","arxiv_id":"2207.01407","repositories_listed":0,"syntology":null},{"url":null,"slug":"wireless-channel-prediction-in-partially","title":"Wireless Channel Prediction in Partially Observed Environments","date":"2022-07-03","arxiv_id":"2207.00934","repositories_listed":0,"syntology":null}],"record_sha256":"2129f9531b076eef24c88c665b858712a992310ff490607a3167d5f1842dc51f","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}