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Neural Causal Models for Counterfactual Identification and Estimation

Neural Causal Models for Counterfactual Identification and Estimation

30 September 2022
K. Xia
Yushu Pan
Elias Bareinboim
    CML
ArXivPDFHTML

Papers citing "Neural Causal Models for Counterfactual Identification and Estimation"

27 / 27 papers shown
Title
Interpretable Neural Causal Models with TRAM-DAGs
Interpretable Neural Causal Models with TRAM-DAGs
Beate Sick
Oliver Durr
CML
48
1
0
20 Mar 2025
CausalMan: A physics-based simulator for large-scale causality
CausalMan: A physics-based simulator for large-scale causality
Nicholas Tagliapietra
J. Luettin
Lavdim Halilaj
Moritz Willig
Tim Pychynski
Kristian Kersting
CML
45
0
0
18 Feb 2025
The Fragility of Fairness: Causal Sensitivity Analysis for Fair Machine
  Learning
The Fragility of Fairness: Causal Sensitivity Analysis for Fair Machine Learning
Jake Fawkes
Nic Fishman
Mel Andrews
Zachary C. Lipton
19
1
0
12 Oct 2024
Latent 3D Brain MRI Counterfactual
Latent 3D Brain MRI Counterfactual
Wei Peng
Tian Xia
Fabio De Sousa Ribeiro
Tomas Bosschieter
Ehsan Adeli
Qingyu Zhao
Ben Glocker
K. Pohl
CML
MedIm
34
1
0
09 Sep 2024
Estimating Causal Effects from Learned Causal Networks
Estimating Causal Effects from Learned Causal Networks
Anna K. Raichev
Alexander Ihler
Jin Tian
Rina Dechter
CML
9
3
0
26 Aug 2024
Consistency of Neural Causal Partial Identification
Consistency of Neural Causal Partial Identification
Jiyuan Tan
Jose Blanchet
Vasilis Syrgkanis
CML
19
0
0
24 May 2024
Learning Structural Causal Models through Deep Generative Models:
  Methods, Guarantees, and Challenges
Learning Structural Causal Models through Deep Generative Models: Methods, Guarantees, and Challenges
Audrey Poinsot
Alessandro Leite
Nicolas Chesneau
Michèle Sébag
Marc Schoenauer
38
3
0
08 May 2024
Mitigating attribute amplification in counterfactual image generation
Mitigating attribute amplification in counterfactual image generation
Tian Xia
Mélanie Roschewitz
Fabio De Sousa Ribeiro
Charles Jones
Ben Glocker
CML
MedIm
32
1
0
14 Mar 2024
Hybrid$^2$ Neural ODE Causal Modeling and an Application to Glycemic
  Response
Hybrid2^22 Neural ODE Causal Modeling and an Application to Glycemic Response
Bob Junyi Zou
Matthew E. Levine
D. Zaharieva
Ramesh Johari
Emily Fox
23
4
0
27 Feb 2024
Conditional Generative Models are Sufficient to Sample from Any Causal
  Effect Estimand
Conditional Generative Models are Sufficient to Sample from Any Causal Effect Estimand
Md Musfiqur Rahman
Matt Jordan
Murat Kocaoglu
DiffM
CML
12
0
0
12 Feb 2024
Counterfactual Image Editing
Counterfactual Image Editing
Yushu Pan
Elias Bareinboim
BDL
CML
25
5
0
07 Feb 2024
Neural Causal Abstractions
Neural Causal Abstractions
K. Xia
Elias Bareinboim
CML
NAI
26
5
0
05 Jan 2024
Modular Learning of Deep Causal Generative Models for High-dimensional
  Causal Inference
Modular Learning of Deep Causal Generative Models for High-dimensional Causal Inference
Md Musfiqur Rahman
Murat Kocaoglu
OOD
14
2
0
02 Jan 2024
A Neural Framework for Generalized Causal Sensitivity Analysis
A Neural Framework for Generalized Causal Sensitivity Analysis
Dennis Frauen
F. Imrie
Alicia Curth
Valentyn Melnychuk
Stefan Feuerriegel
M. Schaar
CML
11
10
0
27 Nov 2023
Causal Interpretation of Self-Attention in Pre-Trained Transformers
Causal Interpretation of Self-Attention in Pre-Trained Transformers
R. Y. Rohekar
Yaniv Gurwicz
Shami Nisimov
MILM
18
14
0
31 Oct 2023
A General Neural Causal Model for Interactive Recommendation
A General Neural Causal Model for Interactive Recommendation
Jialin Liu
Xinyan Su
Peng Zhou
Xiangyu Zhao
Jun Li
CML
8
0
0
30 Oct 2023
Towards Causal Foundation Model: on Duality between Causal Inference and
  Attention
Towards Causal Foundation Model: on Duality between Causal Inference and Attention
Jiaqi Zhang
Joel Jennings
Agrin Hilmkil
Nick Pawlowski
Cheng Zhang
Chao Ma
CML
41
13
0
01 Oct 2023
High Fidelity Image Counterfactuals with Probabilistic Causal Models
High Fidelity Image Counterfactuals with Probabilistic Causal Models
Fabio De Sousa Ribeiro
Tian Xia
M. Monteiro
Nick Pawlowski
Ben Glocker
DiffM
11
35
0
27 Jun 2023
Advancing Counterfactual Inference through Nonlinear Quantile Regression
Advancing Counterfactual Inference through Nonlinear Quantile Regression
Shaoan Xie
Biwei Huang
Bin Gu
Tongliang Liu
Kun Zhang
11
1
0
09 Jun 2023
Causal normalizing flows: from theory to practice
Causal normalizing flows: from theory to practice
Adrián Javaloy
Pablo Sánchez-Martín
Isabel Valera
TPM
CML
AI4CE
19
20
0
08 Jun 2023
Partial Counterfactual Identification of Continuous Outcomes with a
  Curvature Sensitivity Model
Partial Counterfactual Identification of Continuous Outcomes with a Curvature Sensitivity Model
Valentyn Melnychuk
Dennis Frauen
Stefan Feuerriegel
6
11
0
02 Jun 2023
Sharp Bounds for Generalized Causal Sensitivity Analysis
Sharp Bounds for Generalized Causal Sensitivity Analysis
Dennis Frauen
Valentyn Melnychuk
Stefan Feuerriegel
CML
20
18
0
26 May 2023
Counterfactual Identifiability of Bijective Causal Models
Counterfactual Identifiability of Bijective Causal Models
Arash Nasr-Esfahany
MohammadIman Alizadeh
Devavrat Shah
CML
BDL
22
26
0
04 Feb 2023
Deep Causal Learning: Representation, Discovery and Inference
Deep Causal Learning: Representation, Discovery and Inference
Zizhen Deng
Xiaolong Zheng
Hu Tian
D. Zeng
CML
BDL
26
11
0
07 Nov 2022
Relating Graph Neural Networks to Structural Causal Models
Relating Graph Neural Networks to Structural Causal Models
Matej Zečević
D. Dhami
Petar Velickovic
Kristian Kersting
AI4CE
CML
53
53
0
09 Sep 2021
Double Reinforcement Learning for Efficient Off-Policy Evaluation in
  Markov Decision Processes
Double Reinforcement Learning for Efficient Off-Policy Evaluation in Markov Decision Processes
Nathan Kallus
Masatoshi Uehara
OffRL
29
180
0
22 Aug 2019
Learning Representations for Counterfactual Inference
Learning Representations for Counterfactual Inference
Fredrik D. Johansson
Uri Shalit
David Sontag
CML
OOD
BDL
205
713
0
12 May 2016
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