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Interventions, Where and How? Experimental Design for Causal Models at Scale
Neural Information Processing Systems (NeurIPS), 2022
3 March 2022
P. Tigas
Yashas Annadani
Andrew Jesson
Bernhard Schölkopf
Y. Gal
Stefan Bauer
CML
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Papers citing
"Interventions, Where and How? Experimental Design for Causal Models at Scale"
38 / 38 papers shown
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Characterization and Learning of Causal Graphs from Hard Interventions
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Efficient Data Selection for Training Genomic Perturbation Models
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When Selection Meets Intervention: Additional Complexities in Causal Discovery
International Conference on Learning Representations (ICLR), 2025
Haoyue Dai
Ignavier Ng
Jianle Sun
Zeyu Tang
Gongxu Luo
Xinshuai Dong
Peter Spirtes
Kun Zhang
CML
416
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10 Mar 2025
Can Large Language Models Help Experimental Design for Causal Discovery?
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Yongqiang Chen
Chenxi Liu
Qianyi Cai
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Bo Han
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Hui Xiong
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426
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03 Mar 2025
CausalMan: A physics-based simulator for large-scale causality
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J. Luettin
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Tim Pychynski
Kristian Kersting
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457
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18 Feb 2025
CORD: Generalizable Cooperation via Role Diversity
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Kefan Su
Jiangxing Wang
Deheng Ye
Zongqing Lu
367
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04 Jan 2025
Graph Agnostic Causal Bayesian Optimisation
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Mengyan Zhang
Seth Flaxman
Sebastian Vollmer
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354
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05 Nov 2024
Simulation-based Benchmarking for Causal Structure Learning in Gene Perturbation Experiments
Luka Kovacevic
Izzy Newsham
Sach Mukherjee
John Whittaker
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247
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0
08 Jul 2024
Bayesian Intervention Optimization for Causal Discovery
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Mingzhou Liu
Xinwei Sun
Wei Wang
Yizhou Wang
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184
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16 Jun 2024
Challenges and Considerations in the Evaluation of Bayesian Causal Discovery
Amir Mohammad Karimi Mamaghan
P. Tigas
Karl Henrik Johansson
Yarin Gal
Yashas Annadani
Stefan Bauer
CML
321
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05 Jun 2024
Amortized Active Causal Induction with Deep Reinforcement Learning
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P. Tigas
Stefan Bauer
Adam Foster
380
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Effective Bayesian Causal Inference via Structural Marginalisation and Autoregressive Orders
Christian Toth
Christian Knoll
Franz Pernkopf
Robert Peharz
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573
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22 Feb 2024
Causal Discovery under Off-Target Interventions
Davin Choo
Kirankumar Shiragur
Caroline Uhler
CML
226
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1
13 Feb 2024
The Essential Role of Causality in Foundation World Models for Embodied AI
Tarun Gupta
Wenbo Gong
Chao Ma
Nick Pawlowski
Agrin Hilmkil
...
Jianfeng Gao
Stefan Bauer
Danica Kragic
Bernhard Schölkopf
Cheng Zhang
327
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06 Feb 2024
CORE: Towards Scalable and Efficient Causal Discovery with Reinforcement Learning
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N. Botteghi
Erman Acar
Aske Plaat
CML
356
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30 Jan 2024
BayesDAG: Gradient-Based Posterior Inference for Causal Discovery
Neural Information Processing Systems (NeurIPS), 2023
Yashas Annadani
Nick Pawlowski
Joel Jennings
Stefan Bauer
Cheng Zhang
Wenbo Gong
CML
BDL
393
37
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26 Jul 2023
Benchmarking Bayesian Causal Discovery Methods for Downstream Treatment Effect Estimation
Chris C. Emezue
Alexandre Drouin
T. Deleu
Stefan Bauer
Yoshua Bengio
CML
409
3
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11 Jul 2023
Intervention Generalization: A View from Factor Graph Models
Neural Information Processing Systems (NeurIPS), 2023
Gecia Bravo Hermsdorff
David S. Watson
Jialin Yu
Jakob Zeitler
Ricardo M. A. Silva
CML
299
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06 Jun 2023
Constrained Causal Bayesian Optimization
International Conference on Machine Learning (ICML), 2023
Virginia Aglietti
Alan Malek
Ira Ktena
Silvia Chiappa
CML
238
9
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31 May 2023
CO-BED: Information-Theoretic Contextual Optimization via Bayesian Experimental Design
International Conference on Machine Learning (ICML), 2023
Desi R. Ivanova
Joel Jennings
Tom Rainforth
Cheng Zhang
Adam Foster
351
4
0
27 Feb 2023
Differentiable Multi-Target Causal Bayesian Experimental Design
International Conference on Machine Learning (ICML), 2023
Yashas Annadani
P. Tigas
Desi R. Ivanova
Andrew Jesson
Y. Gal
Adam Foster
Stefan Bauer
BDL
CML
327
14
0
21 Feb 2023
Sequential Underspecified Instrument Selection for Cause-Effect Estimation
International Conference on Machine Learning (ICML), 2023
Elisabeth Ailer
Jason S. Hartford
Niki Kilbertus
CML
347
5
0
11 Feb 2023
GFlowNets for AI-Driven Scientific Discovery
Digital Discovery (DD), 2023
Moksh Jain
T. Deleu
Jason S. Hartford
Cheng-Hao Liu
Alex Hernandez-Garcia
Yoshua Bengio
AI4CE
381
78
0
01 Feb 2023
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
449
3
0
24 Nov 2022
Federated Causal Discovery From Interventions
Amin Abyaneh
Nino Scherrer
Patrick Schwab
Stefan Bauer
Bernhard Schölkopf
Arash Mehrjou
FedML
292
1
0
07 Nov 2022
Bayesian learning of Causal Structure and Mechanisms with GFlowNets and Variational Bayes
Mizu Nishikawa-Toomey
T. Deleu
Jithendaraa Subramanian
Yoshua Bengio
Laurent Charlin
BDL
CML
433
34
0
04 Nov 2022
Learning Latent Structural Causal Models
Jithendaraa Subramanian
Yashas Annadani
Ivaxi Sheth
Nan Rosemary Ke
T. Deleu
Stefan Bauer
Derek Nowrouzezahrai
Samira Ebrahimi Kahou
CML
269
7
0
24 Oct 2022
Experimental Design for Multi-Channel Imaging via Task-Driven Feature Selection
International Conference on Learning Representations (ICLR), 2022
Stefano B. Blumberg
Paddy J. Slator
Daniel C. Alexander
456
1
0
13 Oct 2022
Active Learning for Optimal Intervention Design in Causal Models
Nature Machine Intelligence (Nat. Mach. Intell.), 2022
Jiaqi Zhang
Louis V. Cammarata
C. Squires
T. Sapsis
Caroline Uhler
CML
368
44
0
10 Sep 2022
A Meta-Reinforcement Learning Algorithm for Causal Discovery
CLEaR (CLEaR), 2022
Andreas Sauter
Erman Acar
Vincent François-Lavet
CML
307
21
0
18 Jul 2022
Latent Variable Models for Bayesian Causal Discovery
Jithendaraa Subramanian
Yashas Annadani
Ivaxi Sheth
Stefan Bauer
Derek Nowrouzezahrai
Samira Ebrahimi Kahou
CML
BDL
202
1
0
12 Jul 2022
On the Generalization and Adaption Performance of Causal Models
Nino Scherrer
Anirudh Goyal
Stefan Bauer
Yoshua Bengio
Nan Rosemary Ke
CML
OOD
BDL
TTA
240
10
0
09 Jun 2022
Active Bayesian Causal Inference
Neural Information Processing Systems (NeurIPS), 2022
Christian Toth
Lars Lorch
Christian Knoll
Andreas Krause
Franz Pernkopf
Robert Peharz
Julius von Kügelgen
318
45
0
04 Jun 2022
Causal Structure Learning: a Combinatorial Perspective
Foundations of Computational Mathematics (FoCM), 2022
C. Squires
Caroline Uhler
CML
541
66
0
02 Jun 2022
A Unified Experiment Design Approach for Cyclic and Acyclic Causal Models
Journal of machine learning research (JMLR), 2022
Ehsan Mokhtarian
Saber Salehkaleybar
AmirEmad Ghassami
Negar Kiyavash
373
6
0
20 May 2022
Stochastic Batch Acquisition: A Simple Baseline for Deep Active Learning
Andreas Kirsch
Sebastian Farquhar
Parmida Atighehchian
Andrew Jesson
Frederic Branchaud-Charron
Y. Gal
469
38
0
22 Jun 2021
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