Learning Causal Semantic Representation for Out-of-Distribution Prediction

3 November 2020

Papers citing "Learning Causal Semantic Representation for Out-of-Distribution Prediction"

9 / 9 papers shown

Title
Towards Generalising Neural Topical Representations Xiaohao Yang He Zhao Dinh Q. Phung Lan Du BDL OOD MedIm 11 1 0 24 Jul 2023
Meta-causal Learning for Single Domain Generalization Jin Chen Zhiqiang Gao Xinxiao Wu Jiebo Luo OOD 21 41 0 07 Apr 2023
GLOBEM Dataset: Multi-Year Datasets for Longitudinal Human Behavior Modeling Generalization Xuhai Xu Han Zhang Yasaman S. Sefidgar Yiyi Ren Xin Liu ... Tim Althoff Margaret E. Morris E. Riskin Jennifer Mankoff A. Dey 24 38 0 04 Nov 2022
Domain-invariant Feature Exploration for Domain Generalization Wang Lu Jindong Wang Haoliang Li Yiqiang Chen Xing Xie OOD 23 69 0 25 Jul 2022
Generalizing to Unseen Domains: A Survey on Domain Generalization Jindong Wang Cuiling Lan Chang-Shu Liu Yidong Ouyang Tao Qin Wang Lu Yiqiang Chen Wenjun Zeng Philip S. Yu OOD 43 1,165 0 02 Mar 2021
Out-of-Distribution Generalization via Risk Extrapolation (REx) David M. Krueger Ethan Caballero J. Jacobsen Amy Zhang Jonathan Binas Dinghuai Zhang Rémi Le Priol Aaron Courville OOD 215 888 0 02 Mar 2020
Weakly-Supervised Disentanglement Without Compromises Francesco Locatello Ben Poole Gunnar Rätsch Bernhard Schölkopf Olivier Bachem Michael Tschannen CoGe OOD DRL 171 311 0 07 Feb 2020
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 250 5,813 0 08 Jul 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 247 9,042 0 06 Jun 2015