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1302.6784
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Counterfactual Probabilities: Computational Methods, Bounds and Applications
Conference on Uncertainty in Artificial Intelligence (UAI), 1994
27 February 2013
Alexander Balke
Judea Pearl
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Papers citing
"Counterfactual Probabilities: Computational Methods, Bounds and Applications"
50 / 76 papers shown
Probabilities of Causation and Root Cause Analysis with Quasi-Markovian Models
Eduardo Rocha Laurentino
Fabio Gagliardi Cozman
Denis Deratani Mauá
Daniel Angelo Esteves Lawand
Davi Goncalves Bezerra Coelho
Lucas Martins Marques
CML
170
0
0
02 Sep 2025
Multilinear and Linear Programs for Partially Identifiable Queries in Quasi-Markovian Structural Causal Models
João P. Arroyo
João G. Rodrigues
Daniel Lawand
Denis Deratani Mauá
Junkyu Lee
Radu Marinescu
Alex Gray
Eduardo Rocha Laurentino
Fabio Gagliardi Cozman
131
1
0
02 Sep 2025
Recover Experimental Data with Selection Bias using Counterfactual Logic
Jingyang He
Shuai Wang
Ang Li
CML
215
0
0
31 May 2025
Counterfactual Strategies for Markov Decision Processes
International Joint Conference on Artificial Intelligence (IJCAI), 2025
Paul Kobialka
Lina Gerlach
Francesco Leofante
E. Ábrahám
S. L. T. Tarifa
E. Johnsen
228
0
0
14 May 2025
A primer on optimal transport for causal inference with observational data
Florian F Gunsilius
OT
CML
350
4
0
10 Mar 2025
Causally Reliable Concept Bottleneck Models
Giovanni De Felice
Arianna Casanova Flores
Francesco De Santis
Silvia Santini
Johannes Schneider
Pietro Barbiero
Alberto Termine
603
9
0
06 Mar 2025
Causal Imitation Learning under Expert-Observable and Expert-Unobservable Confounding
Daqian Shao
Thomas Kleine Buening
Marta Z. Kwiatkowska
CML
362
1
0
11 Feb 2025
Learning Counterfactual Outcomes Under Rank Preservation
Peng Wu
Haoxuan Li
Chunyuan Zheng
Yan Zeng
Jiawei Chen
Yang Liu
Ruocheng Guo
Jianchao Tan
372
4
0
10 Feb 2025
Learning Representations of Instruments for Partial Identification of Treatment Effects
Jonas Schweisthal
Dennis Frauen
Maresa Schröder
Konstantin Hess
Niki Kilbertus
Stefan Feuerriegel
CML
373
2
0
11 Oct 2024
Causal Inference with Latent Variables: Recent Advances and Future Prospectives
Yaochen Zhu
Yinhan He
Jing Ma
Mengxuan Hu
Sheng Li
Jundong Li
CML
349
12
0
20 Jun 2024
Root Cause Analysis of Outliers with Missing Structural Knowledge
William Orchard
Nastaran Okati
Sergio Hernan Garrido Mejia
Patrick Blobaum
Dominik Janzing
588
9
0
07 Jun 2024
Consistency of Neural Causal Partial Identification
Jiyuan Tan
Jose Blanchet
Vasilis Syrgkanis
CML
437
2
0
24 May 2024
Nondeterministic Causal Models
Sander Beckers
380
2
0
22 May 2024
Do No Harm: A Counterfactual Approach to Safe Reinforcement Learning
Sean Vaskov
Wilko Schwarting
Chris Baker
327
2
0
19 May 2024
Counterfactual Image Editing
Yushu Pan
Elias Bareinboim
BDL
CML
360
19
0
07 Feb 2024
Flexible Nonparametric Inference for Causal Effects under the Front-Door Model
Anna Guo
David Benkeser
Razieh Nabi
CML
251
3
0
15 Dec 2023
Tightening Bounds on Probabilities of Causation By Merging Datasets
Numair Sani
Atalanti A. Mastakouri
337
1
0
12 Oct 2023
Scalable Computation of Causal Bounds
International Conference on Machine Learning (ICML), 2023
Madhumitha Shridharan
G. Iyengar
185
6
0
04 Aug 2023
Approximating Counterfactual Bounds while Fusing Observational, Biased and Randomised Data Sources
International Journal of Approximate Reasoning (IJAR), 2023
Marco Zaffalon
Alessandro Antonucci
Rafael Cabañas
David Huber
288
8
0
31 Jul 2023
Results on Counterfactual Invariance
Jake Fawkes
R. Evans
191
4
0
17 Jul 2023
Efficient Computation of Counterfactual Bounds
International Journal of Approximate Reasoning (IJAR), 2023
Marco Zaffalon
Alessandro Antonucci
Rafael Cabañas
David Huber
Dario Azzimonti
399
8
0
17 Jul 2023
Causal Fairness for Outcome Control
Neural Information Processing Systems (NeurIPS), 2023
Drago Plečko
Elias Bareinboim
220
12
0
08 Jun 2023
Partial Counterfactual Identification of Continuous Outcomes with a Curvature Sensitivity Model
Neural Information Processing Systems (NeurIPS), 2023
Valentyn Melnychuk
Dennis Frauen
Stefan Feuerriegel
730
14
0
02 Jun 2023
Bounding probabilities of causation through the causal marginal problem
Numair Sani
Atalanti A. Mastakouri
Dominik Janzing
CML
490
5
0
04 Apr 2023
Counterfactual Identifiability of Bijective Causal Models
International Conference on Machine Learning (ICML), 2023
Arash Nasr-Esfahany
MohammadIman Alizadeh
Devavrat Shah
CML
BDL
534
41
0
04 Feb 2023
Learning to Bound Counterfactual Inference from Observational, Biased and Randomised Data
Marco Zaffalon
Alessandro Antonucci
David Huber
Rafael Cabañas
OOD
CML
248
0
0
06 Dec 2022
On the Complexity of Counterfactual Reasoning
International Joint Conference on Artificial Intelligence (IJCAI), 2022
Yunqiu Han
Yizuo Chen
Adnan Darwiche
209
8
0
24 Nov 2022
Partial counterfactual identification and uplift modeling: theoretical results and real-world assessment
Machine-mediated learning (ML), 2022
Théo Verhelst
Denis Mercier
Jeevan Shrestha
Gianluca Bontempi
CML
190
3
0
14 Nov 2022
Partial Counterfactual Identification for Infinite Horizon Partially Observable Markov Decision Process
Aditya Kelvianto Sidharta
OffRL
129
0
0
31 Aug 2022
Sensitivity Analysis of G-estimators to Invalid Instrumental Variables
Statistics in Medicine (Stat Med), 2022
Valentin Vancak
Arvid Sjolander
CML
182
3
0
11 Aug 2022
Explaining the root causes of unit-level changes
Kailash Budhathoki
George Michailidis
Dominik Janzing
FAtt
226
4
0
26 Jun 2022
Causal Inference with Treatment Measurement Error: A Nonparametric Instrumental Variable Approach
Conference on Uncertainty in Artificial Intelligence (UAI), 2022
Yuchen Zhu
Limor Gultchin
Arthur Gretton
Matt J. Kusner
Ricardo M. A. Silva
CML
188
18
0
18 Jun 2022
Detecting hidden confounding in observational data using multiple environments
Neural Information Processing Systems (NeurIPS), 2022
R. Karlsson
Jesse H. Krijthe
CML
OOD
497
18
0
27 May 2022
Counterfactual Analysis in Dynamic Latent State Models
International Conference on Machine Learning (ICML), 2022
Martin Haugh
Raghav Singal
CML
414
7
0
27 May 2022
Counterfactual harm
Neural Information Processing Systems (NeurIPS), 2022
Jonathan G. Richens
R. Beard
Daniel H. Thompson
493
33
0
27 Apr 2022
The Causal Marginal Polytope for Bounding Treatment Effects
Jakob Zeitler
Ricardo M. A. Silva
306
3
0
28 Feb 2022
Stochastic Causal Programming for Bounding Treatment Effects
CLEaR (CLEaR), 2022
Kirtan Padh
Jakob Zeitler
David S. Watson
Matt J. Kusner
Ricardo M. A. Silva
Niki Kilbertus
CML
522
29
0
22 Feb 2022
Partial Identification with Noisy Covariates: A Robust Optimization Approach
CLEaR (CLEaR), 2022
Wenshuo Guo
Mingzhang Yin
Yixin Wang
Michael I. Jordan
441
20
0
22 Feb 2022
Causal Imitation Learning under Temporally Correlated Noise
International Conference on Machine Learning (ICML), 2022
Gokul Swamy
Sanjiban Choudhury
J. Andrew Bagnell
Zhiwei Steven Wu
CML
250
35
0
02 Feb 2022
Causal Inference Through the Structural Causal Marginal Problem
International Conference on Machine Learning (ICML), 2022
Luigi Gresele
Julius von Kügelgen
Jonas M. Kubler
Elke Kirschbaum
Bernhard Schölkopf
Dominik Janzing
417
28
0
02 Feb 2022
Filtered-CoPhy: Unsupervised Learning of Counterfactual Physics in Pixel Space
International Conference on Learning Representations (ICLR), 2022
Steeven Janny
Fabien Baradel
Natalia Neverova
M. Nadri
Greg Mori
Christian Wolf
CML
265
17
0
01 Feb 2022
Partial Counterfactual Identification from Observational and Experimental Data
International Conference on Machine Learning (ICML), 2021
Junzhe Zhang
Jin Tian
Elias Bareinboim
238
77
0
12 Oct 2021
An Automated Approach to Causal Inference in Discrete Settings
Guilherme Duarte
N. Finkelstein
D. Knox
Jonathan Mummolo
I. Shpitser
409
59
0
28 Sep 2021
Safe Policy Learning through Extrapolation: Application to Pre-trial Risk Assessment
Eli Ben-Michael
D. J. Greiner
Kosuke Imai
Zhichao Jiang
OffRL
548
27
0
22 Sep 2021
The Causal-Neural Connection: Expressiveness, Learnability, and Inference
K. Xia
Kai-Zhan Lee
Yoshua Bengio
Elias Bareinboim
CML
396
136
0
02 Jul 2021
Algorithmic Recourse in Partially and Fully Confounded Settings Through Bounding Counterfactual Effects
Julius von Kügelgen
N. Agarwal
Jakob Zeitler
Afsaneh Mastouri
Bernhard Schölkopf
CML
256
3
0
22 Jun 2021
Neural Networks for Learning Counterfactual G-Invariances from Single Environments
International Conference on Learning Representations (ICLR), 2021
S Chandra Mouli
Bruno Ribeiro
OOD
229
13
0
20 Apr 2021
SBI: A Simulation-Based Test of Identifiability for Bayesian Causal Inference
Sam Witty
David D. Jensen
Vikash K. Mansinghka
CML
199
4
0
23 Feb 2021
Instrumental Variable Value Iteration for Causal Offline Reinforcement Learning
Luofeng Liao
Zuyue Fu
Zhuoran Yang
Yixin Wang
Mladen Kolar
Zhaoran Wang
OffRL
347
40
0
19 Feb 2021
Causal World Models by Unsupervised Deconfounding of Physical Dynamics
Minne Li
Mengyue Yang
Furui Liu
Xu Chen
Zhitang Chen
Jun Wang
SyDa
CML
233
17
0
28 Dec 2020
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