Selecting Data Augmentation for Simulating Interventions

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Selecting Data Augmentation for Simulating Interventions

4 May 2020

Maximilian Ilse

Jakub M. Tomczak

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Papers citing "Selecting Data Augmentation for Simulating Interventions"

9 / 9 papers shown

Title
Predicting is not Understanding: Recognizing and Addressing Underspecification in Machine Learning Damien Teney Maxime Peyrard Ehsan Abbasnejad 115 29 0 06 Jul 2022
Self-Supervised Learning with Data Augmentations Provably Isolates Content from Style Julius von Kügelgen Yash Sharma Luigi Gresele Wieland Brendel Bernhard Schölkopf M. Besserve Francesco Locatello 133 317 0 08 Jun 2021
Out-of-distribution Prediction with Invariant Risk Minimization: The Limitation and An Effective Fix Ruocheng Guo Pengchuan Zhang Hao Liu Emre Kıcıman OOD 80 37 0 16 Jan 2021
Counterfactual Generative Networks Axel Sauer Andreas Geiger OOD BDL CML 102 127 0 15 Jan 2021
Generative Interventions for Causal Learning Chengzhi Mao Augustine Cha Amogh Gupta Hongya Wang Junfeng Yang Carl Vondrick CML OOD 86 66 0 22 Dec 2020
Latent Causal Invariant Model Xinwei Sun Botong Wu Xiangyu Zheng Chang-Shu Liu Wei Chen Tao Qin Tie-Yan Liu OOD CML BDL 93 14 0 04 Nov 2020
Learning Causal Semantic Representation for Out-of-Distribution Prediction Chang-Shu Liu Xinwei Sun Jindong Wang Haoyue Tang Tao Li Tao Qin Wei Chen Tie-Yan Liu CML OODD OOD 153 106 0 03 Nov 2020
Automatic Data Augmentation for Generalization in Deep Reinforcement Learning Roberta Raileanu M. Goldstein Denis Yarats Ilya Kostrikov Rob Fergus OffRL 63 110 0 23 Jun 2020
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 344 945 0 02 Mar 2020