Invariant Risk Minimization

5 July 2019

Papers citing "Invariant Risk Minimization"

50 / 1,404 papers shown

Title
Controllable Prompt Tuning For Balancing Group Distributional Robustness Hoang Phan Andrew Gordon Wilson Qi Lei 43 5 0 05 Mar 2024
OTClean: Data Cleaning for Conditional Independence Violations using Optimal Transport Alireza Pirhadi Mohammad Hossein Moslemi Alexander Cloninger Mostafa Milani Babak Salimi 20 4 0 04 Mar 2024
A Survey on Evaluation of Out-of-Distribution Generalization Han Yu Jiashuo Liu Xingxuan Zhang Jiayun Wu Peng Cui OOD 47 8 0 04 Mar 2024
Improving out-of-distribution generalization in graphs via hierarchical semantic environments Yinhua Piao Sangseon Lee Yijingxiu Lu Sun Kim OOD 39 2 0 04 Mar 2024
Recent Advances, Applications, and Open Challenges in Machine Learning for Health: Reflections from Research Roundtables at ML4H 2023 Symposium Hyewon Jeong Sarah Jabbour Yuzhe Yang Rahul Thapta Hussein Mozannar ... Linying Zhang Harvineet Singh Tom Hartvigsen Helen Zhou Chinasa T. Okolo VLM AI4TS OOD 43 2 0 03 Mar 2024
The Implicit Bias of Heterogeneity towards Invariance: A Study of Multi-Environment Matrix Sensing Yang Xu Yihong Gu Cong Fang 48 0 0 03 Mar 2024
Fine-tuning with Very Large Dropout Jianyu Zhang Léon Bottou 44 1 0 01 Mar 2024
Decompose-and-Compose: A Compositional Approach to Mitigating Spurious Correlation Fahimeh Hosseini Noohdani Parsa Hosseini Aryan Yazdan Parast Hamidreza Yaghoubi Araghi M. Baghshah CoGe OOD 36 6 0 29 Feb 2024
DIGIC: Domain Generalizable Imitation Learning by Causal Discovery Yang Chen Yitao Liang Zhouchen Lin OOD CML 36 0 0 29 Feb 2024
RORA: Robust Free-Text Rationale Evaluation Zhengping Jiang Yining Lu Hanjie Chen Daniel Khashabi Benjamin Van Durme Anqi Liu 53 1 0 28 Feb 2024
DeepDRK: Deep Dependency Regularized Knockoff for Feature Selection Hongyu Shen Yici Yan Zhizhen Zhao 19 0 0 27 Feb 2024
StochCA: A Novel Approach for Exploiting Pretrained Models with Cross-Attention SeungWon Seo Suho Lee Sangheum Hwang 35 0 0 25 Feb 2024
Domain Generalization via Causal Adjustment for Cross-Domain Sentiment Analysis Siyin Wang Jie Zhou Qin Chen Qi Zhang Tao Gui Xuanjing Huang OOD TTA 40 1 0 22 Feb 2024
On the Conflict of Robustness and Learning in Collaborative Machine Learning Mathilde Raynal Carmela Troncoso 27 2 0 21 Feb 2024
Unsupervised Concept Discovery Mitigates Spurious Correlations Md Rifat Arefin Yan Zhang A. Baratin Francesco Locatello Irina Rish Dianbo Liu Kenji Kawaguchi 59 6 0 20 Feb 2024
Spurious Correlations in Machine Learning: A Survey Wenqian Ye Guangtao Zheng Xu Cao Yunsheng Ma Aidong Zhang OOD AAML CML 39 34 0 20 Feb 2024
A Comprehensive Review of Machine Learning Advances on Data Change: A Cross-Field Perspective Jeng-Lin Li Chih-Fan Hsu Ming-Ching Chang Wei-Chao Chen OOD 44 2 0 20 Feb 2024
Learning Conditional Invariances through Non-Commutativity Abhra Chaudhuri Serban Georgescu Anjan Dutta 52 0 0 18 Feb 2024
Graph Out-of-Distribution Generalization via Causal Intervention Qitian Wu Fan Nie Chenxiao Yang Tianyi Bao Junchi Yan OODD OOD AI4CE 40 18 0 18 Feb 2024
Robustness to Subpopulation Shift with Domain Label Noise via Regularized Annotation of Domains Nathan Stromberg Rohan Ayyagari Monica Welfert Sanmi Koyejo Richard Nock Lalitha Sankar 23 3 0 16 Feb 2024
Robust agents learn causal world models Jonathan G. Richens Tom Everitt OOD 122 36 0 16 Feb 2024
Any-Shift Prompting for Generalization over Distributions Zehao Xiao Jiayi Shen Mohammad Mahdi Derakhshani Tianran Ouyang Cees G. M. Snoek OOD VPVLM VLM 45 8 0 15 Feb 2024
Unifying Invariance and Spuriousity for Graph Out-of-Distribution via Probability of Necessity and Sufficiency Xuexin Chen Ruichu Cai Kaitao Zheng Zhifan Jiang Zhengting Huang Zhifeng Hao Zijian Li 24 2 0 14 Feb 2024
Investigating Out-of-Distribution Generalization of GNNs: An Architecture Perspective Kai Guo Hongzhi Wen Wei Jin Yaming Guo Jiliang Tang Yi Chang OOD AI4CE 19 3 0 13 Feb 2024
HYPO: Hyperspherical Out-of-Distribution Generalization Yifei Ming Haoyue Bai Julian Katz-Samuels Yixuan Li OODD OOD 40 9 0 12 Feb 2024
GSINA: Improving Subgraph Extraction for Graph Invariant Learning via Graph Sinkhorn Attention Fangyu Ding Haiyang Wang Zhixuan Chu Tianming Li Zhaoping Hu Junchi Yan AI4CE 19 1 0 11 Feb 2024
For Better or For Worse? Learning Minimum Variance Features With Label Augmentation Muthuraman Chidambaram Rong Ge AAML 18 0 0 10 Feb 2024
Dynamic Graph Information Bottleneck Haonan Yuan Qingyun Sun Xingcheng Fu Cheng Ji Jianxin Li AAML AI4CE 41 8 0 09 Feb 2024
On Provable Length and Compositional Generalization Kartik Ahuja Amin Mansouri OODD 41 7 0 07 Feb 2024
LEVI: Generalizable Fine-tuning via Layer-wise Ensemble of Different Views Yuji Roh Qingyun Liu Huan Gui Zhe Yuan Yujin Tang ... Liang Liu Shuchao Bi Lichan Hong Ed H. Chi Zhe Zhao 43 1 0 07 Feb 2024
Enhancing Compositional Generalization via Compositional Feature Alignment Haoxiang Wang Haozhe Si Huajie Shao Han Zhao 40 1 0 05 Feb 2024
Supervised Algorithmic Fairness in Distribution Shifts: A Survey Minglai Shao Dong Li Chen Zhao Xintao Wu Yujie Lin Qin Tian OOD 31 8 0 02 Feb 2024
Towards Understanding Variants of Invariant Risk Minimization through the Lens of Calibration Kotaro Yoshida Hiroki Naganuma 68 1 0 31 Jan 2024
Graph Fairness Learning under Distribution Shifts Yibo Li Xiao Wang Yujie Xing Shaohua Fan Ruijia Wang Yaoqi Liu Chuan Shi OOD 39 7 0 30 Jan 2024
Continuous Treatment Effect Estimation Using Gradient Interpolation and Kernel Smoothing Lokesh Nagalapatti Akshay Iyer Abir De Sunita Sarawagi CML 27 7 0 27 Jan 2024
Understanding Domain Generalization: A Noise Robustness Perspective Rui Qiao K. H. Low OOD 39 6 0 26 Jan 2024
Graph Contrastive Invariant Learning from the Causal Perspective Yanhu Mo Xiao Wang Shaohua Fan Chuan Shi 32 14 0 23 Jan 2024
WARM: On the Benefits of Weight Averaged Reward Models Alexandre Ramé Nino Vieillard Léonard Hussenot Robert Dadashi Geoffrey Cideron Olivier Bachem Johan Ferret 118 93 0 22 Jan 2024
Medical Image Debiasing by Learning Adaptive Agreement from a Biased Council Luyang Luo Xin Huang Minghao Wang Zhuoyue Wan Hao Chen 32 2 0 22 Jan 2024
AutoFT: Learning an Objective for Robust Fine-Tuning Caroline Choi Yoonho Lee Annie S. Chen Allan Zhou Aditi Raghunathan Chelsea Finn OOD 52 0 0 18 Jan 2024
HCVP: Leveraging Hierarchical Contrastive Visual Prompt for Domain Generalization Guanglin Zhou Zhongyi Han Shiming Chen Erdun Gao Liming Zhu Tongliang Liu Lina Yao Anton van den Hengel 32 3 0 18 Jan 2024
Enhancing Evolving Domain Generalization through Dynamic Latent Representations Binghui Xie Yongqiang Chen Jiaqi Wang Kaiwen Zhou Bo Han Wei Meng James Cheng 41 5 0 16 Jan 2024
Learning Generalizable Models via Disentangling Spurious and Enhancing Potential Correlations Na Wang Lei Qi Jintao Guo Yinghuan Shi Yang Gao OOD 32 4 0 11 Jan 2024
StarCraftImage: A Dataset For Prototyping Spatial Reasoning Methods For Multi-Agent Environments Sean Kulinski Nicholas R. Waytowich James Z. Hare David I. Inouye 25 3 0 09 Jan 2024
Robust Calibration For Improved Weather Prediction Under Distributional Shift Sankalp Gilda Neel Bhandari Wendy Mak Andrea Panizza UQCV OOD 11 1 0 08 Jan 2024
Preserving Silent Features for Domain Generalization Chujie Zhao Tianren Zhang Feng Chen 23 0 0 06 Jan 2024
Prompt-driven Latent Domain Generalization for Medical Image Classification Siyuan Yan Chi Liu Zhen Yu Lie Ju Dwarikanath Mahapatra B. Betz‐Stablein Victoria Mar Monika Janda Peter Soyer Zongyuan Ge OOD VLM MedIm 35 7 0 05 Jan 2024
Modular Learning of Deep Causal Generative Models for High-dimensional Causal Inference Md Musfiqur Rahman Murat Kocaoglu OOD 35 2 0 02 Jan 2024
Causal State Distillation for Explainable Reinforcement Learning Wenhao Lu Xufeng Zhao Thilo Fryen Jae Hee Lee Mengdi Li S. Magg Stefan Wermter CML 41 2 0 30 Dec 2023
Out of the Ordinary: Spectrally Adapting Regression for Covariate Shift Benjamin Eyre Elliot Creager David Madras Antonio Torralba Katherine Heller OOD OODD 40 1 0 29 Dec 2023