Invariant Risk Minimization

5 July 2019

Papers citing "Invariant Risk Minimization"

50 / 1,407 papers shown

Title
Doge Tickets: Uncovering Domain-general Language Models by Playing Lottery Tickets Yi Yang Chen Zhang Benyou Wang Dawei Song LRM 31 6 0 20 Jul 2022
Invariant Feature Learning for Generalized Long-Tailed Classification Kaihua Tang Mingyuan Tao Jiaxin Qi Zhenguang Liu Hanwang Zhang VLM 32 53 0 19 Jul 2022
Assaying Out-Of-Distribution Generalization in Transfer Learning F. Wenzel Andrea Dittadi Peter V. Gehler Carl-Johann Simon-Gabriel Max Horn ... Chris Russell Thomas Brox Bernt Schiele Bernhard Schölkopf Francesco Locatello OOD OODD AAML 67 71 0 19 Jul 2022
Generalizing Goal-Conditioned Reinforcement Learning with Variational Causal Reasoning Wenhao Ding Haohong Lin Bo Li Ding Zhao LRM 28 37 0 19 Jul 2022
Calibrated ensembles can mitigate accuracy tradeoffs under distribution shift Ananya Kumar Tengyu Ma Percy Liang Aditi Raghunathan UQCV OODD OOD 49 38 0 18 Jul 2022
Contrastive Adapters for Foundation Model Group Robustness Michael Zhang Christopher Ré VLM 23 62 0 14 Jul 2022
Breaking Correlation Shift via Conditional Invariant Regularizer Mingyang Yi Ruoyu Wang Jiacheng Sun Zhenguo Li Zhi-Ming Ma OODD 25 5 0 14 Jul 2022
Wakeword Detection under Distribution Shifts S. Parthasarathi Lu Zeng Christin Jose Joe Wang 8 1 0 13 Jul 2022
Grounding Aleatoric Uncertainty for Unsupervised Environment Design Minqi Jiang Michael Dennis Jack Parker-Holder Andrei Lupu Heinrich Küttler Edward Grefenstette Tim Rocktaschel Jakob N. Foerster 48 13 0 11 Jul 2022
Probing Classifiers are Unreliable for Concept Removal and Detection Abhinav Kumar Chenhao Tan Amit Sharma AAML 36 21 0 08 Jul 2022
Harnessing Out-Of-Distribution Examples via Augmenting Content and Style Zhuo Huang Xiaobo Xia Li Shen Bo Han Biwei Huang Chen Gong Tongliang Liu OODD 38 46 0 07 Jul 2022
Predicting is not Understanding: Recognizing and Addressing Underspecification in Machine Learning Damien Teney Maxime Peyrard Ehsan Abbasnejad 43 28 0 06 Jul 2022
Predicting Out-of-Domain Generalization with Neighborhood Invariance Nathan Ng Neha Hulkund Kyunghyun Cho Marzyeh Ghassemi OOD 32 4 0 05 Jul 2022
Invariant and Transportable Representations for Anti-Causal Domain Shifts Yibo Jiang Victor Veitch OOD 131 32 0 04 Jul 2022
Identifying the Context Shift between Test Benchmarks and Production Data Matthew Groh OOD 26 8 0 03 Jul 2022
Learning to Increase the Power of Conditional Randomization Tests Shalev Shaer Yaniv Romano CML 40 2 0 03 Jul 2022
Shifts 2.0: Extending The Dataset of Real Distributional Shifts A. Malinin A. Athanasopoulos M. Barakovic Meritxell Bach Cuadra Mark Gales ... Francesco La Rosa Eli Sivena V. Tsarsitalidis Efi Tsompopoulou E. Volf OOD 30 28 0 30 Jun 2022
Verification and search algorithms for causal DAGs Davin Choo Kirankumar Shiragur Arnab Bhattacharyya CML 19 10 0 30 Jun 2022
Towards out of distribution generalization for problems in mechanics Lingxiao Yuan Harold S. Park Emma Lejeune OOD AI4CE 36 17 0 29 Jun 2022
Distilling Model Failures as Directions in Latent Space Saachi Jain Hannah Lawrence Ankur Moitra Aleksander Madry 23 90 0 29 Jun 2022
When Does Group Invariant Learning Survive Spurious Correlations? Yimeng Chen Ruibin Xiong Zhiming Ma Yanyan Lan OOD CML 43 21 0 29 Jun 2022
Towards a Grounded Theory of Causation for Embodied AI Taco S. Cohen CML 33 8 0 28 Jun 2022
On how to avoid exacerbating spurious correlations when models are overparameterized Tina Behnia Ke Wang Christos Thrampoulidis 44 2 0 25 Jun 2022
Gated Domain Units for Multi-source Domain Generalization Simon Foll Alina Dubatovka Eugen Ernst Siu Lun Chau Martin Maritsch Patrik Okanovic Gudrun Thater J. M. Buhmann Felix Wortmann Krikamol Muandet OOD 48 4 0 24 Jun 2022
On Certifying and Improving Generalization to Unseen Domains Akshay Mehra B. Kailkhura Pin-Yu Chen Jihun Hamm OOD 29 4 0 24 Jun 2022
Variational Causal Dynamics: Discovering Modular World Models from Interventions Anson Lei Bernhard Schölkopf Ingmar Posner CML 19 8 0 22 Jun 2022
Learning Debiased Classifier with Biased Committee Nayeong Kim Sehyun Hwang SungSoo Ahn Jaesik Park Suha Kwak CML 36 54 0 22 Jun 2022
Fighting Fire with Fire: Avoiding DNN Shortcuts through Priming Chuan Wen Jianing Qian Jierui Lin Jiaye Teng Dinesh Jayaraman Yang Gao AAML 26 17 0 22 Jun 2022
Mitigating Data Heterogeneity in Federated Learning with Data Augmentation Artur Back de Luca Guojun Zhang Xi Chen Yaoliang Yu FedML 24 30 0 20 Jun 2022
Test-time image-to-image translation ensembling improves out-of-distribution generalization in histopathology Marin Scalbert Maria Vakalopoulou Florent Couzinié-Devy 30 13 0 20 Jun 2022
Supervision Adaptation Balancing In-distribution Generalization and Out-of-distribution Detection Zhilin Zhao LongBing Cao Kun-Yu Lin 29 4 0 19 Jun 2022
Finding Diverse and Predictable Subgraphs for Graph Domain Generalization Junchi Yu Jian Liang Ran He OOD 28 11 0 19 Jun 2022
Motley: Benchmarking Heterogeneity and Personalization in Federated Learning Shan-shan Wu Tian Li Zachary B. Charles Yu Xiao Ziyu Liu Zheng Xu Virginia Smith FedML 50 44 0 18 Jun 2022
Disentangling Model Multiplicity in Deep Learning Ari Heljakka Martin Trapp Arno Solin Arno Solin 46 4 0 17 Jun 2022
How Robust is Unsupervised Representation Learning to Distribution Shift? Yuge Shi Imant Daunhawer Julia E. Vogt Philip Torr Amartya Sanyal OOD 42 25 0 17 Jun 2022
Learning Fair Representation via Distributional Contrastive Disentanglement Changdae Oh Heeji Won Junhyuk So Taero Kim Yewon Kim Hosik Choi Kyungwoo Song FaML CoGe CML DRL 27 40 0 17 Jun 2022
Reframed GES with a Neural Conditional Dependence Measure Xinwei Shen Shengyu Zhu Jiji Zhang Shoubo Hu Zhitang Chen CML 10 3 0 17 Jun 2022
GOOD: A Graph Out-of-Distribution Benchmark Shurui Gui Xiner Li Limei Wang Shuiwang Ji OOD 43 116 0 16 Jun 2022
Domain Generalization via Selective Consistency Regularization for Time Series Classification Wenyu Zhang Mohamed Ragab Chuan-Sheng Foo OOD AI4TS 27 2 0 16 Jun 2022
Modeling the Data-Generating Process is Necessary for Out-of-Distribution Generalization Jivat Neet Kaur Emre Kıcıman Amit Sharma UQCV OOD 30 25 0 15 Jun 2022
Improving generalization by mimicking the human visual diet Spandan Madan You Li Mengmi Zhang Hanspeter Pfister Gabriel Kreiman 22 2 0 15 Jun 2022
Pareto Invariant Risk Minimization: Towards Mitigating the Optimization Dilemma in Out-of-Distribution Generalization Yongqiang Chen Kaiwen Zhou Yatao Bian Binghui Xie Bing Wu ... Kaili Ma Han Yang P. Zhao Bo Han James Cheng OOD OODD 11 35 0 15 Jun 2022
Improving Diversity with Adversarially Learned Transformations for Domain Generalization Tejas Gokhale Rushil Anirudh Jayaraman J. Thiagarajan B. Kailkhura Chitta Baral Yezhou Yang 27 28 0 15 Jun 2022
Disentangled Federated Learning for Tackling Attributes Skew via Invariant Aggregation and Diversity Transferring Zhengquan Luo Yunlong Wang Zilei Wang Zhenan Sun Tieniu Tan FedML 11 42 0 14 Jun 2022
Invariant Structure Learning for Better Generalization and Causal Explainability Yunhao Ge Sercan O. Arik Jinsung Yoon Ao Xu Laurent Itti Tomas Pfister OOD CML 34 2 0 13 Jun 2022
INDIGO: Intrinsic Multimodality for Domain Generalization Puneet Mangla Shivam Chandhok Milan Aggarwal V. Balasubramanian Balaji Krishnamurthy VLM 46 2 0 13 Jun 2022
Regularization Penalty Optimization for Addressing Data Quality Variance in OoD Algorithms Runpeng Yu Hong Zhu Kaican Li Lanqing Hong Rui Zhang Nan Ye Shao-Lun Huang Xiuqiang He 34 6 0 12 Jun 2022
Learning to Detect with Constant False Alarm Rate Tzvi Diskin Uri Okun A. Wiesel 24 8 0 12 Jun 2022
Causal Balancing for Domain Generalization Xinyi Wang Michael Stephen Saxon Jiachen Li Hongyang R. Zhang Kun Zhang William Yang Wang OOD CML 42 21 0 10 Jun 2022
Sample-Efficient Reinforcement Learning in the Presence of Exogenous Information Yonathan Efroni Dylan J. Foster Dipendra Kumar Misra A. Krishnamurthy John Langford OffRL 31 25 0 09 Jun 2022