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Treatment effect estimation with disentangled latent factors
v1v2v3 (latest)

Treatment effect estimation with disentangled latent factors

AAAI Conference on Artificial Intelligence (AAAI), 2020
29 January 2020
Weijia Zhang
Lin Liu
Jiuyong Li
    CML
ArXiv (abs)PDFHTML

Papers citing "Treatment effect estimation with disentangled latent factors"

50 / 56 papers shown
Text Rationalization for Robust Causal Effect Estimation
Text Rationalization for Robust Causal Effect Estimation
Lijinghua Zhang
Hengrui Cai
CML
237
0
0
05 Dec 2025
GDR-learners: Orthogonal Learning of Generative Models for Potential Outcomes
GDR-learners: Orthogonal Learning of Generative Models for Potential Outcomes
Valentyn Melnychuk
Stefan Feuerriegel
123
0
0
26 Sep 2025
Counterfactual Probabilistic Diffusion with Expert Models
Counterfactual Probabilistic Diffusion with Expert Models
Wenhao Mu
Zhi Cao
Mehmed Uludag
Alexander Rodríguez
DiffM
233
1
0
18 Aug 2025
Multi-Treatment-DML: Causal Estimation for Multi-Dimensional Continuous Treatments with Monotonicity Constraints in Personal Loan Risk Optimization
Multi-Treatment-DML: Causal Estimation for Multi-Dimensional Continuous Treatments with Monotonicity Constraints in Personal Loan Risk Optimization
Kexin Zhao
Bo Wang
Cuiying Zhao
Tongyao Wan
202
0
0
04 Aug 2025
Federated Instrumental Variable Analysis via Federated Generalized Method of Moments
Federated Instrumental Variable Analysis via Federated Generalized Method of Moments
Geetika
Somya Tyagi
Bapi Chatterjee
FedML
238
0
0
27 May 2025
A Generative Framework for Causal Estimation via Importance-Weighted Diffusion Distillation
A Generative Framework for Causal Estimation via Importance-Weighted Diffusion Distillation
Xinran Song
Tianyu Chen
Mingyuan Zhou
DiffMCML
327
0
0
16 May 2025
Long-Term Individual Causal Effect Estimation via Identifiable Latent Representation Learning
Long-Term Individual Causal Effect Estimation via Identifiable Latent Representation LearningInternational Joint Conference on Artificial Intelligence (IJCAI), 2025
Ruichu Cai
Junjie Wan
Weilin Chen
Zeqin Yang
Zijian Li
Peng Zhen
Jiecheng Guo
CML
579
1
0
08 May 2025
Causal Effect Estimation under Networked Interference without Networked Unconfoundedness Assumption
Causal Effect Estimation under Networked Interference without Networked Unconfoundedness Assumption
Weilin Chen
Ruichu Cai
Jie Qiao
Yuguang Yan
José Miguel Hernández-Lobato
CML
408
2
0
27 Feb 2025
Disentangled Representation Learning for Causal Inference with
  Instruments
Disentangled Representation Learning for Causal Inference with InstrumentsIEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2024
Debo Cheng
Jiuyong Li
Lin Liu
Ziqi Xu
Weijia Zhang
Qingbin Liu
T. Le
OODCML
294
13
0
05 Dec 2024
Leaning Time-Varying Instruments for Identifying Causal Effects in
  Time-Series Data
Leaning Time-Varying Instruments for Identifying Causal Effects in Time-Series Data
Debo Cheng
Ziqi Xu
Jiuyong Li
Lin Liu
T. Le
Xudong Guo
Shichao Zhang
CML
389
0
0
26 Nov 2024
CaTs and DAGs: Integrating Directed Acyclic Graphs with Transformers for Causally Constrained Predictions
CaTs and DAGs: Integrating Directed Acyclic Graphs with Transformers for Causally Constrained Predictions
M. Vowels
Mathieu Rochat
S. Akbari
CMLGNNOOD
708
0
0
18 Oct 2024
DiffPO: A causal diffusion model for learning distributions of potential
  outcomes
DiffPO: A causal diffusion model for learning distributions of potential outcomesNeural Information Processing Systems (NeurIPS), 2024
Yuchen Ma
Valentyn Melnychuk
Jonas Schweisthal
Stefan Feuerriegel
DiffM
404
16
0
11 Oct 2024
Causal GNNs: A GNN-Driven Instrumental Variable Approach for Causal
  Inference in Networks
Causal GNNs: A GNN-Driven Instrumental Variable Approach for Causal Inference in Networks
Xiaojing Du
Feiyu Yang
Wentao Gao
Xiongren Chen
CML
275
3
0
13 Sep 2024
Estimating Conditional Average Treatment Effects via Sufficient
  Representation Learning
Estimating Conditional Average Treatment Effects via Sufficient Representation LearningInternational Joint Conference on Artificial Intelligence (IJCAI), 2024
Pengfei Shi
Wei Zhong
Xinyu Zhang
Ningtao Wang
Xing Fu
Weiqiang Wang
Yin Jin
CMLBDL
155
1
0
30 Aug 2024
Causal Effect Estimation using identifiable Variational AutoEncoder with
  Latent Confounders and Post-Treatment Variables
Causal Effect Estimation using identifiable Variational AutoEncoder with Latent Confounders and Post-Treatment Variables
Yang Xie
Ziqi Xu
Debo Cheng
Jiuyong Li
Lin Liu
Yinghao Zhang
Zaiwen Feng
CMLBDL
225
1
0
13 Aug 2024
Generalized Encouragement-Based Instrumental Variables for
  Counterfactual Regression
Generalized Encouragement-Based Instrumental Variables for Counterfactual Regression
Anpeng Wu
Kun Kuang
Ruoxuan Xiong
Xiangwei Chen
Zexu Sun
Fei Wu
Kun Zhang
CML
207
0
0
10 Aug 2024
On the Effects of Irrelevant Variables in Treatment Effect Estimation
  with Deep Disentanglement
On the Effects of Irrelevant Variables in Treatment Effect Estimation with Deep DisentanglementEuropean Conference on Artificial Intelligence (ECAI), 2024
Ahmad Saeed Khan
Erik Schaffernicht
J. A. Stork
CML
426
1
0
29 Jul 2024
Causal Inference with Latent Variables: Recent Advances and Future
  Prospectives
Causal Inference with Latent Variables: Recent Advances and Future Prospectives
Yaochen Zhu
Yinhan He
Jing Ma
Mengxuan Hu
Sheng Li
Jundong Li
CML
337
12
0
20 Jun 2024
Self-Distilled Disentangled Learning for Counterfactual Prediction
Self-Distilled Disentangled Learning for Counterfactual PredictionKnowledge Discovery and Data Mining (KDD), 2024
Xinshu Li
Mingming Gong
Lina Yao
CML
304
3
0
09 Jun 2024
Enhancing predictive imaging biomarker discovery through treatment
  effect analysis
Enhancing predictive imaging biomarker discovery through treatment effect analysis
Shuhan Xiao
Lukas Klein
Jens Petersen
Philipp Vollmuth
Paul F. Jaeger
Klaus H. Maier-Hein
275
1
0
04 Jun 2024
Disentangled Representation via Variational AutoEncoder for Continuous
  Treatment Effect Estimation
Disentangled Representation via Variational AutoEncoder for Continuous Treatment Effect Estimation
Ruijing Cui
Jianbin Sun
Bingyu He
Kewei Yang
Bingfeng Ge
221
0
0
04 Jun 2024
Conditional Generative Models are Sufficient to Sample from Any Causal
  Effect Estimand
Conditional Generative Models are Sufficient to Sample from Any Causal Effect EstimandNeural Information Processing Systems (NeurIPS), 2024
Md Musfiqur Rahman
Matt Jordan
Murat Kocaoglu
DiffMCML
301
4
0
12 Feb 2024
Modular Learning of Deep Causal Generative Models for High-dimensional
  Causal Inference
Modular Learning of Deep Causal Generative Models for High-dimensional Causal InferenceInternational Conference on Machine Learning (ICML), 2024
Md Musfiqur Rahman
Murat Kocaoglu
OOD
277
9
0
02 Jan 2024
Adversarially Balanced Representation for Continuous Treatment Effect
  Estimation
Adversarially Balanced Representation for Continuous Treatment Effect Estimation
Amirreza Kazemi
Martin Ester
CMLOOD
256
6
0
17 Dec 2023
Disentangled Latent Representation Learning for Tackling the Confounding
  M-Bias Problem in Causal Inference
Disentangled Latent Representation Learning for Tackling the Confounding M-Bias Problem in Causal InferenceIndustrial Conference on Data Mining (IDM), 2023
Debo Cheng
Yang Xie
Ziqi Xu
Jiuyong Li
Lin Liu
Jixue Liu
Yinghao Zhang
Zaiwen Feng
CMLBDL
261
4
0
08 Dec 2023
Causal Inference from Text: Unveiling Interactions between Variables
Causal Inference from Text: Unveiling Interactions between Variables
Yuxiang Zhou
Yulan He
CML
314
8
0
09 Nov 2023
Estimating treatment effects from single-arm trials via latent-variable
  modeling
Estimating treatment effects from single-arm trials via latent-variable modelingInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2023
Manuel Haussmann
Tran Minh Son Le
Viivi Halla-aho
Samu Kurki
Jussi Leinonen
Miika Koskinen
Samuel Kaski
Harri Lähdesmäki
CML
413
0
0
06 Nov 2023
Counterfactual Prediction Under Selective Confounding
Counterfactual Prediction Under Selective ConfoundingEuropean Conference on Artificial Intelligence (ECAI), 2023
Sohaib Kiani
Jared Barton
Jon Sushinsky
Lynda Heimbach
Bo Luo
CML
301
2
0
21 Oct 2023
High Dimensional Causal Inference with Variational Backdoor Adjustment
High Dimensional Causal Inference with Variational Backdoor Adjustment
Daniel Israel
Aditya Grover
Karen Ullrich
CML
218
3
0
09 Oct 2023
Causal Inference with Conditional Front-Door Adjustment and Identifiable
  Variational Autoencoder
Causal Inference with Conditional Front-Door Adjustment and Identifiable Variational AutoencoderInternational Conference on Learning Representations (ICLR), 2023
Ziqi Xu
Debo Cheng
Jiuyong Li
Jixue Liu
Lin Liu
Kui Yu
CML
234
21
0
03 Oct 2023
SLEM: Machine Learning for Path Modeling and Causal Inference with Super
  Learner Equation Modeling
SLEM: Machine Learning for Path Modeling and Causal Inference with Super Learner Equation Modeling
M. Vowels
CML
431
3
0
08 Aug 2023
Variational Counterfactual Prediction under Runtime Domain Corruption
Variational Counterfactual Prediction under Runtime Domain CorruptionIEEE Transactions on Knowledge and Data Engineering (TKDE), 2023
Hechuan Wen
Tong Chen
L. K. Chai
S. Sadiq
Junbin Gao
Hongzhi Yin
OOD
279
3
0
23 Jun 2023
Dynamic Inter-treatment Information Sharing for Individualized Treatment
  Effects Estimation
Dynamic Inter-treatment Information Sharing for Individualized Treatment Effects EstimationInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2023
V. Chauhan
Jiandong Zhou
Ghadeer O. Ghosheh
Soheila Molaei
David Clifton
416
14
0
25 May 2023
Causal Effect Estimation with Variational AutoEncoder and the Front Door
  Criterion
Causal Effect Estimation with Variational AutoEncoder and the Front Door Criterion
Ziqi Xu
Debo Cheng
Jiuyong Li
Jixue Liu
Lin Liu
Kui Yu
CML
245
2
0
24 Apr 2023
Linking a predictive model to causal effect estimation
Linking a predictive model to causal effect estimation
Jiuyong Li
Lin Liu
Ziqi Xu
Ha Xuan Tran
T. Le
Jixue Liu
CML
212
0
0
10 Apr 2023
Towards Learning and Explaining Indirect Causal Effects in Neural
  Networks
Towards Learning and Explaining Indirect Causal Effects in Neural NetworksAAAI Conference on Artificial Intelligence (AAAI), 2023
Abbaavaram Gowtham Reddy
Saketh Bachu
Harsh Nilesh Pathak
Ben Godfrey
V. Balasubramanian
V. Varshaneya
Satya Narayanan Kar
CML
376
2
0
24 Mar 2023
DR-VIDAL -- Doubly Robust Variational Information-theoretic Deep Adversarial Learning for Counterfactual Prediction and Treatment Effect Estimation on Real World Data
DR-VIDAL -- Doubly Robust Variational Information-theoretic Deep Adversarial Learning for Counterfactual Prediction and Treatment Effect Estimation on Real World DataAmerican Medical Informatics Association Annual Symposium (AMIA), 2021
Shantanu Ghosh
Zheng Feng
Jiang Bian
Kevin R. B. Butler
M. Prosperi
CMLOODBDL
243
2
0
07 Mar 2023
Disentangled Representation for Causal Mediation Analysis
Disentangled Representation for Causal Mediation AnalysisAAAI Conference on Artificial Intelligence (AAAI), 2023
Ziqi Xu
Debo Cheng
Jiuyong Li
Jixue Liu
Lin Liu
Ke Wang
CML
237
14
0
19 Feb 2023
Causal Effect Estimation: Recent Advances, Challenges, and Opportunities
Causal Effect Estimation: Recent Advances, Challenges, and Opportunities
Zhixuan Chu
Jia-Bin Huang
Ruopeng Li
Wei Chu
Sheng Li
CMLOOD
244
9
0
02 Feb 2023
Instrumental Variables in Causal Inference and Machine Learning: A
  Survey
Instrumental Variables in Causal Inference and Machine Learning: A SurveyACM Computing Surveys (ACM CSUR), 2022
Anpeng Wu
Kun Kuang
Ruoxuan Xiong
Leilei Gan
SyDaCML
281
17
0
12 Dec 2022
Causal Inference with Conditional Instruments using Deep Generative
  Models
Causal Inference with Conditional Instruments using Deep Generative ModelsAAAI Conference on Artificial Intelligence (AAAI), 2022
Debo Cheng
Ziqi Xu
Jiuyong Li
Lin Liu
Jixue Liu
T. Le
CML
158
22
0
29 Nov 2022
Confounder Balancing for Instrumental Variable Regression with Latent
  Variable
Confounder Balancing for Instrumental Variable Regression with Latent Variable
Anpeng Wu
Kun Kuang
Ruoxuan Xiong
Bo Li
Leilei Gan
CML
322
1
0
18 Nov 2022
NESTER: An Adaptive Neurosymbolic Method for Causal Effect Estimation
NESTER: An Adaptive Neurosymbolic Method for Causal Effect EstimationAAAI Conference on Artificial Intelligence (AAAI), 2022
Abbavaram Gowtham Reddy
V. Balasubramanian
CML
436
1
0
08 Nov 2022
Deep Causal Learning: Representation, Discovery and Inference
Deep Causal Learning: Representation, Discovery and Inference
Zizhen Deng
Xiaolong Zheng
Hu Tian
D. Zeng
CMLBDL
438
21
0
07 Nov 2022
Adversarial De-confounding in Individualised Treatment Effects
  Estimation
Adversarial De-confounding in Individualised Treatment Effects EstimationInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2022
Vinod Kumar Chauhan
Soheila Molaei
Marzia Hoque Tania
Anshul Thakur
T. Zhu
David Clifton
CML
320
17
0
19 Oct 2022
Long-term Causal Effects Estimation via Latent Surrogates Representation
  Learning
Long-term Causal Effects Estimation via Latent Surrogates Representation LearningNeural Networks (NN), 2022
Ruichu Cai
Weilin Chen
Zeqin Yang
Shu Wan
Chen Zheng
Xiaoqing Yang
Jiecheng Guo
CMLBDL
367
12
0
09 Aug 2022
Variational Temporal Deconfounder for Individualized Treatment Effect
  Estimation from Longitudinal Observational Data
Variational Temporal Deconfounder for Individualized Treatment Effect Estimation from Longitudinal Observational Data
Zheng Feng
M. Prosperi
Jiang Bian
CML
221
0
0
23 Jul 2022
A Causal Research Pipeline and Tutorial for Psychologists and Social
  Scientists
A Causal Research Pipeline and Tutorial for Psychologists and Social ScientistsPsychological methods (Psychol Methods), 2022
M. Vowels
CML
335
6
0
10 Jun 2022
Learning Disentangled Representations for Counterfactual Regression via
  Mutual Information Minimization
Learning Disentangled Representations for Counterfactual Regression via Mutual Information MinimizationAnnual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2022
Min Cheng
Xinru Liao
Quanlian Liu
Bin Ma
Jian Xu
Bo Zheng
CML
260
35
0
02 Jun 2022
Deep Multi-Modal Structural Equations For Causal Effect Estimation With
  Unstructured Proxies
Deep Multi-Modal Structural Equations For Causal Effect Estimation With Unstructured ProxiesNeural Information Processing Systems (NeurIPS), 2022
Shachi Deshpande
Kaiwen Wang
Dhruv Sreenivas
Zheng Li
Volodymyr Kuleshov
CMLSyDa
445
14
0
18 Mar 2022
12
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