The Risks of Invariant Risk Minimization

12 October 2020

Andrej Risteski

Papers citing "The Risks of Invariant Risk Minimization"

50 / 78 papers shown

Title
Partial Transportability for Domain Generalization Kasra Jalaldoust Alexis Bellot Elias Bareinboim OOD 77 5 0 30 Mar 2025
Achievable distributional robustness when the robust risk is only partially identified Julia Kostin Nicola Gnecco Fanny Yang 71 3 0 04 Feb 2025
Causality Pursuit from Heterogeneous Environments via Neural Adversarial Invariance Learning Yihong Gu Cong Fang Peter Bühlmann Jianqing Fan CML OOD 70 2 0 31 Dec 2024
Compositional Risk Minimization Divyat Mahajan Mohammad Pezeshki Ioannis Mitliagkas Kartik Ahuja Pascal Vincent Pascal Vincent 26 3 0 08 Oct 2024
Unsupervised Domain Adaptation Via Data Pruning Andrea Napoli Paul White 36 1 0 18 Sep 2024
Invariant Graph Learning Meets Information Bottleneck for Out-of-Distribution Generalization Wenyu Mao Jiancan Wu Haoyang Liu Yongduo Sui Xiang Wang OOD 39 2 0 03 Aug 2024
Invariant Correlation of Representation with Label: Enhancing Domain Generalization in Noisy Environments Gaojie Jin Ronghui Mu Xinping Yi Xiaowei Huang Lijun Zhang 67 0 0 01 Jul 2024
Fine-Grained Domain Generalization with Feature Structuralization Wenlong Yu Dongyue Chen Qilong Wang Qinghua Hu 36 0 0 13 Jun 2024
Loss Gradient Gaussian Width based Generalization and Optimization Guarantees A. Banerjee Qiaobo Li Yingxue Zhou 44 0 0 11 Jun 2024
Feature contamination: Neural networks learn uncorrelated features and fail to generalize Tianren Zhang Chujie Zhao Guanyu Chen Yizhou Jiang Feng Chen OOD MLT OODD 77 3 0 05 Jun 2024
A Textbook Remedy for Domain Shifts: Knowledge Priors for Medical Image Analysis Yue Yang Mona Gandhi Yufei Wang Yifan Wu Michael S. Yao Christopher Callison-Burch James C. Gee Mark Yatskar 50 3 0 23 May 2024
Preserving Silent Features for Domain Generalization Chujie Zhao Tianren Zhang Feng Chen 23 0 0 06 Jan 2024
Bayesian Domain Invariant Learning via Posterior Generalization of Parameter Distributions Shiyu Shen Bin Pan Tianyang Shi Tao Li Zhenwei Shi BDL OOD 29 1 0 25 Oct 2023
Gradual Domain Adaptation: Theory and Algorithms Yifei He Haoxiang Wang Bo Li Han Zhao CLL 49 5 0 20 Oct 2023
Data Augmentations for Improved (Large) Language Model Generalization Amir Feder Yoav Wald Claudia Shi S. Saria David M. Blei OOD CML 32 7 0 19 Oct 2023
Conditionally Invariant Representation Learning for Disentangling Cellular Heterogeneity H. Aliee Ferdinand Kapl Soroor Hediyeh-zadeh Fabian J. Theis CML 23 6 0 02 Jul 2023
Towards Characterizing Domain Counterfactuals For Invertible Latent Causal Models Zeyu Zhou Ruqi Bai Sean Kulinski Murat Kocaoglu David I. Inouye CML 24 1 0 20 Jun 2023
An Invariant Learning Characterization of Controlled Text Generation Carolina Zheng Claudia Shi Keyon Vafa Amir Feder David M. Blei OOD 30 8 0 31 May 2023
Conformal Inference for Invariant Risk Minimization Wenlu Tang Zicheng Liu 24 0 0 22 May 2023
Patchwork Learning: A Paradigm Towards Integrative Analysis across Diverse Biomedical Data Sources Suraj Rajendran Weishen Pan M. Sabuncu Yong Chen Jiayu Zhou Fei Wang 54 14 0 10 May 2023
Reliable learning in challenging environments Maria-Florina Balcan Steve Hanneke Rattana Pukdee Dravyansh Sharma OOD 30 4 0 06 Apr 2023
CAusal and collaborative proxy-tasKs lEarning for Semi-Supervised Domain Adaptation Wenqiao Zhang Changshuo Liu Can Cui Beng Chin Ooi CML 27 0 0 30 Mar 2023
Domain Generalization via Nuclear Norm Regularization Zhenmei Shi Yifei Ming Ying Fan Frederic Sala Yingyu Liang 30 12 0 13 Mar 2023
Diagnosing Model Performance Under Distribution Shift Tiffany Cai Hongseok Namkoong Steve Yadlowsky 34 27 0 03 Mar 2023
Learning Optimal Features via Partial Invariance Moulik Choraria Ibtihal Ferwana Ankur Mani L. Varshney OOD 26 2 0 28 Jan 2023
Model Agnostic Sample Reweighting for Out-of-Distribution Learning Xiao Zhou Yong Lin Renjie Pi Weizhong Zhang Renzhe Xu Peng Cui Tong Zhang OODD 31 60 0 24 Jan 2023
Target Conditioned Representation Independence (TCRI); From Domain-Invariant to Domain-General Representations Olawale Salaudeen Oluwasanmi Koyejo 32 2 0 21 Dec 2022
On the Connection between Invariant Learning and Adversarial Training for Out-of-Distribution Generalization Shiji Xin Yifei Wang Jingtong Su Yisen Wang OOD 21 7 0 18 Dec 2022
Malign Overfitting: Interpolation Can Provably Preclude Invariance Yoav Wald G. Yona Uri Shalit Y. Carmon 17 5 0 28 Nov 2022
Exploiting Personalized Invariance for Better Out-of-distribution Generalization in Federated Learning Xueyang Tang Song Guo Jie M. Zhang FedML OODD OOD 36 3 0 21 Nov 2022
A Survey on Causal Representation Learning and Future Work for Medical Image Analysis Chang-Tien Lu OOD BDL CML MedIm 26 0 0 28 Oct 2022
Learning Invariant Representations under General Interventions on the Response Kang Du Yu Xiang OOD 22 8 0 22 Aug 2022
Artifact-Based Domain Generalization of Skin Lesion Models Alceu Bissoto Catarina Barata Eduardo Valle Sandra Avila MedIm AI4CE 35 13 0 20 Aug 2022
Repeated Environment Inference for Invariant Learning Aayush Mishra Anqi Liu BDL OOD 25 0 0 26 Jul 2022
When Does Group Invariant Learning Survive Spurious Correlations? Yimeng Chen Ruibin Xiong Zhiming Ma Yanyan Lan OOD CML 19 20 0 29 Jun 2022
GOOD: A Graph Out-of-Distribution Benchmark Shurui Gui Xiner Li Limei Wang Shuiwang Ji OOD 22 115 0 16 Jun 2022
Domain Generalization via Selective Consistency Regularization for Time Series Classification Wenyu Zhang Mohamed Ragab Chuan-Sheng Foo OOD AI4TS 19 2 0 16 Jun 2022
PAC Generalization via Invariant Representations Advait Parulekar Karthikeyan Shanmugam Sanjay Shakkottai 35 3 0 30 May 2022
The Missing Invariance Principle Found -- the Reciprocal Twin of Invariant Risk Minimization Dongsung Huh A. Baidya OOD 28 8 0 29 May 2022
Causal Machine Learning for Healthcare and Precision Medicine Pedro Sanchez J. Voisey Tian Xia Hannah I. Watson Alison Q. OÑeil Sotirios A. Tsaftaris OOD CML 42 109 0 23 May 2022
Correcting Confounding via Random Selection of Background Variables You-Lin Chen Lenon Minorics Dominik Janzing CML 27 4 0 04 Feb 2022
Discovering Invariant Rationales for Graph Neural Networks Yingmin Wu Xiang Wang An Zhang Xiangnan He Tat-Seng Chua OOD AI4CE 99 224 0 30 Jan 2022
Conditional entropy minimization principle for learning domain invariant representation features Thuan Q. Nguyen Boyang Lyu Prakash Ishwar matthias. scheutz Shuchin Aeron OOD 27 7 0 25 Jan 2022
Debiased Graph Neural Networks with Agnostic Label Selection Bias Shaohua Fan Xiao Wang Chuan Shi Kun Kuang Nian Liu Bai Wang AI4CE 36 38 0 19 Jan 2022
Causal Attention for Interpretable and Generalizable Graph Classification Yongduo Sui Xiang Wang Jiancan Wu Min-Bin Lin Xiangnan He Tat-Seng Chua CML OOD 17 152 0 30 Dec 2021
Balancing Fairness and Robustness via Partial Invariance Moulik Choraria Ibtihal Ferwana Ankur Mani L. Varshney OOD 30 1 0 17 Dec 2021
Measure and Improve Robustness in NLP Models: A Survey Xuezhi Wang Haohan Wang Diyi Yang 139 130 0 15 Dec 2021
Towards Robust and Adaptive Motion Forecasting: A Causal Representation Perspective Yuejiang Liu Riccardo Cadei Jonas Schweizer Sherwin Bahmani Alexandre Alahi OOD TTA 35 51 0 29 Nov 2021
Towards Principled Disentanglement for Domain Generalization Hanlin Zhang Yi-Fan Zhang Weiyang Liu Adrian Weller Bernhard Schölkopf Eric P. Xing OOD 31 112 0 27 Nov 2021
Exploration of Dark Chemical Genomics Space via Portal Learning: Applied to Targeting the Undruggable Genome and COVID-19 Anti-Infective Polypharmacology Tian Cai Li Xie Muge Chen Yang Liu Di He Shuo-feng Zhang C. Mura P. Bourne Lei Xie OOD 21 4 0 23 Nov 2021