{"total":21,"rows":[{"id":"2203.05818","title":"ZIN: When and How to Learn Invariance Without Environment Partition?","created":"2022-03-11","cited_by_count":58,"area":null},{"id":"2403.01874","title":"A Survey on Evaluation of Out-of-Distribution Generalization","created":"2024-03-04","cited_by_count":21,"area":null},{"id":"2111.02355","title":"A Theoretical Analysis on Independence-driven Importance Weighting for Covariate-shift Generalization","created":"2021-11-03","cited_by_count":19,"area":null},{"id":"2304.11862","title":"Universal Domain Adaptation via Compressive Attention Matching","created":"2023-04-24","cited_by_count":15,"area":null},{"id":"2212.00992","title":"Stable Learning via Sparse Variable Independence","created":"2022-12-02","cited_by_count":13,"area":null},{"id":"2205.12753","title":"An Empirical Study on Distribution Shift Robustness From the Perspective of Pre-Training and Data Augmentation","created":"2022-05-25","cited_by_count":11,"area":null},{"id":"2206.14917","title":"Towards out of distribution generalization for problems in mechanics","created":"2022-06-29","cited_by_count":11,"area":null},{"id":"2403.06606","title":"Distributionally Generative Augmentation for Fair Facial Attribute Classification","created":"2024-03-11","cited_by_count":8,"area":null},{"id":"2305.04466","title":"Generalized Universal Domain Adaptation with Generative Flow Networks","created":"2023-05-08","cited_by_count":7,"area":null},{"id":"2403.01773","title":"Improving out-of-distribution generalization in graphs via hierarchical semantic environments","created":"2024-03-04","cited_by_count":5,"area":null},{"id":"2206.09380","title":"Supervision Adaptation Balancing In-distribution Generalization and Out-of-distribution Detection","created":"2022-06-19","cited_by_count":4,"area":null},{"id":"2305.15889","title":"Quantitatively Measuring and Contrastively Exploring Heterogeneity for Domain Generalization","created":"2023-05-25","cited_by_count":4,"area":null},{"id":"2308.04706","title":"Pareto Invariant Representation Learning for Multimedia Recommendation","created":"2023-08-09","cited_by_count":3,"area":null},{"id":"2308.08778","title":"Environment Diversification with Multi-head Neural Network for Invariant Learning","created":"2023-08-17","cited_by_count":3,"area":null},{"id":"2203.15549","title":"Invariance Learning based on Label Hierarchy","created":"2022-03-29","cited_by_count":1,"area":null},{"id":"2305.15431","title":"Exploring and Exploiting Data Heterogeneity in Recommendation","created":"2023-05-21","cited_by_count":1,"area":null},{"id":"2307.11972","title":"Out-of-Distribution Optimality of Invariant Risk Minimization","created":"2023-07-22","cited_by_count":1,"area":null},{"id":"2504.17314","title":"Class-Conditional Distribution Balancing for Group Robust Classification","created":"2025-04-24","cited_by_count":1,"area":null},{"id":"2210.16034","title":"A Survey on Causal Representation Learning and Future Work for Medical Image Analysis","created":"2022-10-28","cited_by_count":0,"area":null},{"id":"2407.01749","title":"Invariant Correlation of Representation with Label: Enhancing Domain Generalization in Noisy Environments","created":"2024-07-01","cited_by_count":0,"area":null},{"id":"2506.00969","title":"Data Heterogeneity Modeling for Trustworthy Machine Learning","created":"2025-06-01","cited_by_count":0,"area":null}],"next_cursor":null}