Interventions, Where and How? Experimental Design for Causal Models at
Scale

Interventions, Where and How? Experimental Design for Causal Models at Scale

3 March 2022

Yashas Annadani

Bernhard Schölkopf

Stefan Bauer

Papers citing "Interventions, Where and How? Experimental Design for Causal Models at Scale"

7 / 7 papers shown

Title
Characterization and Learning of Causal Graphs from Hard Interventions Zihan Zhou Muhammad Qasim Elahi Murat Kocaoglu CML 66 0 0 02 May 2025
Efficient Data Selection for Training Genomic Perturbation Models G. Panagopoulos J. Lutzeyer Sofiane Ennadir Michalis Vazirgiannis Jun Pang 58 0 0 18 Mar 2025
CORD: Generalizable Cooperation via Role Diversity Kanefumi Matsuyama Kefan Su Jiangxing Wang Deheng Ye Zongqing Lu 35 0 0 04 Jan 2025
Effective Bayesian Causal Inference via Structural Marginalisation and Autoregressive Orders Christian Toth Christian Knoll Franz Pernkopf Robert Peharz CML 38 1 0 22 Feb 2024
Benchmarking Bayesian Causal Discovery Methods for Downstream Treatment Effect Estimation Chris C. Emezue Alexandre Drouin T. Deleu Stefan Bauer Yoshua Bengio CML 13 2 0 11 Jul 2023
$Trust Your $\nabla$: Gradient-based Intervention Targeting for Causal Discovery$ Trust Your $\nabla$ : Gradient-based Intervention Targeting for Causal Discovery Mateusz Olko Michal Zajac A. Nowak Nino Scherrer Yashas Annadani Stefan Bauer Lukasz Kucinski Piotr Milos CML 17 2 0 24 Nov 2022
BCD Nets: Scalable Variational Approaches for Bayesian Causal Discovery Chris Cundy Aditya Grover Stefano Ermon CML 32 71 0 06 Dec 2021