{"total":40,"rows":[{"id":"2106.13799","title":"Assessing Generalization of SGD via Disagreement","created":"2021-06-25","cited_by_count":117,"area":null},{"id":"2111.13171","title":"Intrinsic Dimension, Persistent Homology and Generalization in Neural Networks","created":"2021-11-25","cited_by_count":70,"area":null},{"id":"2109.02355","title":"A Farewell to the Bias-Variance Tradeoff? An Overview of the Theory of Overparameterized Machine Learning","created":"2021-09-06","cited_by_count":57,"area":null},{"id":"2106.03314","title":"Measuring Generalization with Optimal Transport","created":"2021-06-07","cited_by_count":25,"area":null},{"id":"2207.01725","title":"How Much More Data Do I Need? Estimating Requirements for Downstream Tasks","created":"2022-07-04","cited_by_count":23,"area":null},{"id":"2111.05529","title":"Understanding the Generalization Benefit of Model Invariance from a Data Perspective","created":"2021-11-10","cited_by_count":22,"area":null},{"id":"2202.01627","title":"Non-Vacuous Generalisation Bounds for Shallow Neural Networks","created":"2022-02-03","cited_by_count":22,"area":null},{"id":"2106.00734","title":"Post-mortem on a deep learning contest: a Simpson's paradox and the complementary roles of scale metrics versus shape metrics","created":"2021-06-01","cited_by_count":19,"area":null},{"id":"2107.03955","title":"On Margins and Derandomisation in PAC-Bayes","created":"2021-07-08","cited_by_count":19,"area":null},{"id":"2202.02842","title":"Evaluating natural language processing models with generalization metrics that do not need access to any training or testing data","created":"2022-02-06","cited_by_count":19,"area":null},{"id":"2210.01234","title":"Optimizing Data Collection for Machine Learning","created":"2022-10-03","cited_by_count":15,"area":null},{"id":"2106.04765","title":"Predicting Deep Neural Network Generalization with Perturbation Response Curves","created":"2021-06-09","cited_by_count":14,"area":null},{"id":"2203.12330","title":"Predicting the generalization gap in neural networks using topological data analysis","created":"2022-03-23","cited_by_count":9,"area":null},{"id":"2312.05840","title":"Topological Data Analysis for Neural Network Analysis: A Comprehensive Survey","created":"2023-12-10","cited_by_count":9,"area":null},{"id":"2411.06919","title":"Understanding Generalization in Quantum Machine Learning with Margins","created":"2024-11-11","cited_by_count":7,"area":null},{"id":"2111.14212","title":"On Predicting Generalization using GANs","created":"2021-11-28","cited_by_count":6,"area":null},{"id":"2201.09209","title":"Weight Expansion: A New Perspective on Dropout and Generalization","created":"2022-01-23","cited_by_count":6,"area":null},{"id":"2406.09908","title":"What Does Softmax Probability Tell Us about Classifiers Ranking Across Diverse Test Conditions?","created":"2024-06-14","cited_by_count":6,"area":null},{"id":"2208.06028","title":"Gaussian Process Surrogate Models for Neural Networks","created":"2022-08-11","cited_by_count":5,"area":null},{"id":"2110.05702","title":"Auditing Robot Learning for Safety and Compliance during Deployment","created":"2021-10-12","cited_by_count":4,"area":null},{"id":"2207.02093","title":"Predicting Out-of-Domain Generalization with Neighborhood Invariance","created":"2022-07-05","cited_by_count":4,"area":null},{"id":"2308.15466","title":"Input margins can predict generalization too","created":"2023-08-29","cited_by_count":4,"area":null},{"id":"2406.04047","title":"Slicing Mutual Information Generalization Bounds for Neural Networks","created":"2024-06-06","cited_by_count":4,"area":null},{"id":"2104.03469","title":"Gi and Pal Scores: Deep Neural Network Generalization Statistics","created":"2021-04-08","cited_by_count":3,"area":null},{"id":"2206.00823","title":"Beyond accuracy: generalization properties of bio-plausible temporal credit assignment rules","created":"2022-06-02","cited_by_count":3,"area":null},{"id":"2504.18072","title":"A Model Zoo on Phase Transitions in Neural Networks","created":"2025-04-25","cited_by_count":3,"area":null},{"id":"2103.03328","title":"Evaluation of Complexity Measures for Deep Learning Generalization in Medical Image Analysis","created":"2021-03-04","cited_by_count":2,"area":null},{"id":"2110.02863","title":"Exploring the Common Principal Subspace of Deep Features in Neural Networks","created":"2021-10-06","cited_by_count":2,"area":null},{"id":"2110.12259","title":"In Search of Probeable Generalization Measures","created":"2021-10-23","cited_by_count":2,"area":null},{"id":"2210.05673","title":"Performance Deterioration of Deep Learning Models after Clinical Deployment: A Case Study with Auto-segmentation for Definitive Prostate Cancer Radiotherapy","created":"2022-10-11","cited_by_count":2,"area":null},{"id":"2502.05242","title":"Beyond External Monitors: Enhancing Transparency of Large Language Models for Easier Monitoring","created":"2025-02-07","cited_by_count":2,"area":null},{"id":"2106.10653","title":"Practical Assessment of Generalization Performance Robustness for Deep Networks via Contrastive Examples","created":"2021-06-20","cited_by_count":1,"area":null},{"id":"2305.15563","title":"Fantastic DNN Classifiers and How to Identify them without Data","created":"2023-05-24","cited_by_count":1,"area":null},{"id":"2409.01498","title":"A practical generalization metric for deep networks benchmarking","created":"2024-09-02","cited_by_count":1,"area":null},{"id":"2603.19852","title":"Failure Modes for Deep Learning-Based Online Mapping: How to Measure and Address Them","created":"2026-03-20","cited_by_count":1,"area":null},{"id":"2110.08922","title":"Explaining generalization in deep learning: progress and fundamental limits","created":"2021-10-17","cited_by_count":0,"area":null},{"id":"2308.04870","title":"Decorrelating neurons using persistence","created":"2023-08-09","cited_by_count":0,"area":null},{"id":"2411.04695","title":"Is network fragmentation a useful complexity measure?","created":"2024-11-07","cited_by_count":0,"area":null},{"id":"2503.02129","title":"Path Regularization: A Near-Complete and Optimal Nonasymptotic Generalization Theory for Multilayer Neural Networks and Double Descent Phenomenon","created":"2025-03-03","cited_by_count":0,"area":null},{"id":"2603.09257","title":"Transductive Generalization via Optimal Transport and Its Application to Graph Node Classification","created":"2026-03-10","cited_by_count":0,"area":null}],"next_cursor":null}