{"total":33,"rows":[{"id":"2206.15306","title":"Transfer Learning with Deep Tabular Models","created":"2022-06-30","cited_by_count":52,"area":null},{"id":"2504.16109","title":"Representation Learning for Tabular Data: A Comprehensive Survey","created":"2025-04-17","cited_by_count":36,"area":null},{"id":"2401.08552","title":"Explaining Time Series via Contrastive and Locally Sparse Perturbations","created":"2024-01-16","cited_by_count":22,"area":null},{"id":"2306.04785","title":"Interpretable Deep Clustering for Tabular Data","created":"2023-06-07","cited_by_count":19,"area":null},{"id":"2306.12330","title":"ProtoGate: Prototype-based Neural Networks with Global-to-local Feature Selection for Tabular Biomedical Data","created":"2023-06-21","cited_by_count":18,"area":null},{"id":"2501.15638","title":"A Comprehensive Survey on Self-Interpretable Neural Networks","created":"2025-01-26","cited_by_count":18,"area":null},{"id":"2505.18125","title":"TabSTAR: A Tabular Foundation Model for Tabular Data with Text Fields","created":"2025-05-23","cited_by_count":18,"area":null},{"id":"2309.03800","title":"Pareto Frontiers in Neural Feature Learning: Data, Compute, Width, and Luck","created":"2023-09-07","cited_by_count":13,"area":null},{"id":"2502.03391","title":"Explain Yourself, Briefly! Self-Explaining Neural Networks with Concise Sufficient Reasons","created":"2025-02-05","cited_by_count":12,"area":null},{"id":"2509.11259","title":"ICR-RL: Deep Reinforcement Learning via In-Context Regression","created":"2025-09-14","cited_by_count":8,"area":null},{"id":"2312.14254","title":"Contextual Feature Selection with Conditional Stochastic Gates","created":"2023-12-21","cited_by_count":7,"area":null},{"id":"2211.06302","title":"GCondNet: A Novel Method for Improving Neural Networks on Small High-Dimensional Tabular Data","created":"2022-11-11","cited_by_count":6,"area":null},{"id":"2211.15616","title":"Weight Predictor Network with Feature Selection for Small Sample Tabular Biomedical Data","created":"2022-11-28","cited_by_count":6,"area":null},{"id":"2302.00878","title":"The Contextual Lasso: Sparse Linear Models via Deep Neural Networks","created":"2023-02-02","cited_by_count":6,"area":null},{"id":"2303.09381","title":"Multi-modal Differentiable Unsupervised Feature Selection","created":"2023-03-16","cited_by_count":5,"area":null},{"id":"2511.06961","title":"Hybrid Autoencoders for Tabular Data: Leveraging Model-Based Augmentation in Low-Label Settings","created":"2025-11-10","cited_by_count":5,"area":null},{"id":"2109.03099","title":"Optimizing model-agnostic Random Subspace ensembles","created":"2021-09-07","cited_by_count":3,"area":null},{"id":"2407.09790","title":"Team up GBDTs and DNNs: Advancing Efficient and Effective Tabular Prediction with Tree-hybrid MLPs","created":"2024-07-13","cited_by_count":3,"area":null},{"id":"2207.08574","title":"ManiFeSt: Manifold-based Feature Selection for Small Data Sets","created":"2022-07-18","cited_by_count":2,"area":null},{"id":"2312.13240","title":"Efficient Verification-Based Face Identification","created":"2023-12-20","cited_by_count":1,"area":null},{"id":"2402.17599","title":"DAGnosis: Localized Identification of Data Inconsistencies using Structures","created":"2024-02-26","cited_by_count":1,"area":null},{"id":"2406.06634","title":"Sparse Binarization for Fast Keyword Spotting","created":"2024-06-09","cited_by_count":1,"area":null},{"id":"2504.11977","title":"Leveraging Machine Learning Models to Predict the Outcome of Digital Medical Triage Interviews","created":"2025-04-16","cited_by_count":1,"area":null},{"id":"2510.21113","title":"Distributionally Robust Feature Selection","created":"2025-10-24","cited_by_count":1,"area":null},{"id":"2605.03430","title":"DynaTab: Dynamic Feature Ordering as Neural Rewiring for High-Dimensional Tabular Data","created":"2026-05-05","cited_by_count":1,"area":null},{"id":"2306.00528","title":"Neuronal Cell Type Classification using Deep Learning","created":"2023-06-01","cited_by_count":0,"area":null},{"id":"2306.11481","title":"Learning Locally Interpretable Rule Ensemble","created":"2023-06-20","cited_by_count":0,"area":null},{"id":"2402.05680","title":"Interpretable classifiers for tabular data via discretization and feature selection","created":"2024-02-08","cited_by_count":0,"area":null},{"id":"2412.18234","title":"Conditional Deep Canonical Time Warping","created":"2024-12-24","cited_by_count":0,"area":null},{"id":"2503.13304","title":"AutoNFS: Automatic Neural Feature Selection","created":"2025-03-17","cited_by_count":0,"area":null},{"id":"2508.08646","title":"P-CAFE: Personalized Cost-Aware Incremental Feature Selection For Electronic Health Records","created":"2025-08-12","cited_by_count":0,"area":null},{"id":"2510.01758","title":"Unsupervised Dynamic Feature Selection for Robust Latent Spaces in Vision Tasks","created":"2025-10-02","cited_by_count":0,"area":null},{"id":"2608.02887","title":"Population-Robust Feature Selection via Generalized Welfare Optimization","created":"2026-08-03","cited_by_count":0,"area":null}],"next_cursor":null}