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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
P. Tigas
Yashas Annadani
Andrew Jesson
Bernhard Schölkopf
Y. Gal
Stefan Bauer
    CML
ArXivPDFHTML

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
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
Efficient Data Selection for Training Genomic Perturbation Models
G. Panagopoulos
J. Lutzeyer
Sofiane Ennadir
Michalis Vazirgiannis
Jun Pang
56
0
0
18 Mar 2025
CORD: Generalizable Cooperation via Role Diversity
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
Effective Bayesian Causal Inference via Structural Marginalisation and Autoregressive Orders
Christian Toth
Christian Knoll
Franz Pernkopf
Robert Peharz
CML
35
1
0
22 Feb 2024
Benchmarking Bayesian Causal Discovery Methods for Downstream Treatment
  Effect Estimation
Benchmarking Bayesian Causal Discovery Methods for Downstream Treatment Effect Estimation
Chris C. Emezue
Alexandre Drouin
T. Deleu
Stefan Bauer
Yoshua Bengio
CML
8
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
14
2
0
24 Nov 2022
BCD Nets: Scalable Variational Approaches for Bayesian Causal Discovery
BCD Nets: Scalable Variational Approaches for Bayesian Causal Discovery
Chris Cundy
Aditya Grover
Stefano Ermon
CML
32
71
0
06 Dec 2021
1