Active Invariant Causal Prediction: Experiment Selection through Stability

10 June 2020

Papers citing "Active Invariant Causal Prediction: Experiment Selection through Stability"

11 / 11 papers shown

Title
Federated Adapter on Foundation Models: An Out-Of-Distribution Approach Yiyuan Yang Guodong Long Dinesh Manocha Qinghua Lu Shanshan Ye Jing Jiang OODD 222 1 0 02 May 2025
Characterization and Greedy Learning of Gaussian Structural Causal Models under Unknown Interventions Juan L. Gamella Armeen Taeb C. Heinze-Deml Peter Buhlmann CML 94 8 0 13 Mar 2025
Achievable distributional robustness when the robust risk is only partially identified Julia Kostin Nicola Gnecco Fanny Yang 73 3 0 04 Feb 2025
Targeted Sequential Indirect Experiment Design Elisabeth Ailer Niclas Dern Jason S. Hartford Niki Kilbertus 46 1 0 30 May 2024
Sequential Underspecified Instrument Selection for Cause-Effect Estimation Elisabeth Ailer Jason S. Hartford Niki Kilbertus CML 27 3 0 11 Feb 2023
Exploiting Personalized Invariance for Better Out-of-distribution Generalization in Federated Learning Xueyang Tang Song Guo Jie Zhang FedML OODD OOD 36 3 0 21 Nov 2022
Interventions, Where and How? Experimental Design for Causal Models at Scale P. Tigas Yashas Annadani Andrew Jesson Bernhard Schölkopf Y. Gal Stefan Bauer CML 36 48 0 03 Mar 2022
Invariant Ancestry Search Phillip B. Mogensen Nikolaj Thams J. Peters 31 5 0 02 Feb 2022
Automated causal inference in application to randomized controlled clinical trials Ji Q. Wu N. Horeweg M. de Bruyn R. Nout I. Jürgenliemk-Schulz ... H. Nijman V. Smit T. Bosse C. Creutzberg V. Koelzer CML 34 14 0 15 Jan 2022
Learning Neural Causal Models with Active Interventions Nino Scherrer O. Bilaniuk Yashas Annadani Anirudh Goyal Patrick Schwab Bernhard Schölkopf Michael C. Mozer Yoshua Bengio Stefan Bauer Nan Rosemary Ke CML 48 42 0 06 Sep 2021
Towards Out-Of-Distribution Generalization: A Survey Jiashuo Liu Zheyan Shen Yue He Xingxuan Zhang Renzhe Xu Han Yu Peng Cui CML OOD 59 517 0 31 Aug 2021