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Learning Representations for Counterfactual Inference
v1v2v3 (latest)

Learning Representations for Counterfactual Inference

12 May 2016
Fredrik D. Johansson
Uri Shalit
David Sontag
    CMLOODBDL
ArXiv (abs)PDFHTML

Papers citing "Learning Representations for Counterfactual Inference"

50 / 432 papers shown
Causality for Large Language Models
Causality for Large Language Models
Anpeng Wu
Kun Kuang
Minqin Zhu
Yingrong Wang
Yujia Zheng
Kairong Han
Yangqiu Song
Guangyi Chen
Leilei Gan
Kun Zhang
LRM
325
17
0
20 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
383
15
0
11 Oct 2024
Are causal effect estimations enough for optimal recommendations under
  multitreatment scenarios?
Are causal effect estimations enough for optimal recommendations under multitreatment scenarios?
Sherly Alfonso-Sánchez
Kristina P. Sendova
Cristián Bravo
CML
148
0
0
07 Oct 2024
Stabilized Neural Prediction of Potential Outcomes in Continuous Time
Stabilized Neural Prediction of Potential Outcomes in Continuous TimeInternational Conference on Learning Representations (ICLR), 2024
Konstantin Hess
Stefan Feuerriegel
512
3
0
04 Oct 2024
Learning Personalized Treatment Decisions in Precision Medicine:
  Disentangling Treatment Assignment Bias in Counterfactual Outcome Prediction
  and Biomarker Identification
Learning Personalized Treatment Decisions in Precision Medicine: Disentangling Treatment Assignment Bias in Counterfactual Outcome Prediction and Biomarker Identification
Michael Vollenweider
Manuel Schürch
Chiara Rohrer
Gabriele Gut
Michael Krauthammer
Andreas Wicki
CML
278
0
0
01 Oct 2024
Optimizing Treatment Allocation in the Presence of Interference
Optimizing Treatment Allocation in the Presence of InterferenceEuropean Journal of Operational Research (EJOR), 2024
Daan Caljon
Jente Van Belle
Jeroen Berrevoets
Wouter Verbeke
289
2
0
30 Sep 2024
Ads Supply Personalization via Doubly Robust Learning
Ads Supply Personalization via Doubly Robust LearningInternational Conference on Information and Knowledge Management (CIKM), 2024
Wei Shi
Chen Fu
Qi Xu
Sanjian Chen
Jizhe Zhang
Qinqin Zhu
Zhigang Hua
Shuang Yang
OffRL
216
2
0
29 Sep 2024
Towards Representation Learning for Weighting Problems in Design-Based
  Causal Inference
Towards Representation Learning for Weighting Problems in Design-Based Causal InferenceConference on Uncertainty in Artificial Intelligence (UAI), 2024
Oscar Clivio
Avi Feller
Chris Holmes
CMLOOD
257
3
0
24 Sep 2024
Benchmarking Estimators for Natural Experiments: A Novel Dataset and a
  Doubly Robust Algorithm
Benchmarking Estimators for Natural Experiments: A Novel Dataset and a Doubly Robust AlgorithmNeural Information Processing Systems (NeurIPS), 2024
R. Teal Witter
Christopher Musco
224
1
0
06 Sep 2024
Causal Rule Forest: Toward Interpretable and Precise Treatment Effect
  Estimation
Causal Rule Forest: Toward Interpretable and Precise Treatment Effect EstimationIEEE International Conference on Information Reuse and Integration (IRI), 2024
Chan Hsu
Jun-Ting Wu
Yihuang Kang
CML
105
1
0
27 Aug 2024
Identifying treatment response subgroups in observational time-to-event data
Identifying treatment response subgroups in observational time-to-event data
Vincent Jeanselme
Chang Ho Yoon
Fabian Falck
Brian D. M. Tom
Jessica Barrett
OODCML
494
0
0
06 Aug 2024
Conformal Diffusion Models for Individual Treatment Effect Estimation
  and Inference
Conformal Diffusion Models for Individual Treatment Effect Estimation and Inference
Hengrui Cai
Huaqing Jin
Lexin Li
226
1
0
02 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
330
1
0
29 Jul 2024
Causal Interventional Prediction System for Robust and Explainable
  Effect Forecasting
Causal Interventional Prediction System for Robust and Explainable Effect ForecastingInternational Conference on Information and Knowledge Management (CIKM), 2024
Zhixuan Chu
Hui Ding
Guang Zeng
Shiyu Wang
Yiming Li
CML
210
2
0
29 Jul 2024
MiranDa: Mimicking the Learning Processes of Human Doctors to Achieve
  Causal Inference for Medication Recommendation
MiranDa: Mimicking the Learning Processes of Human Doctors to Achieve Causal Inference for Medication Recommendation
Ziheng Wang
Xinhe Li
H. Momma
Stefan Köpsell
CML
245
0
0
23 Jul 2024
Estimating Distributional Treatment Effects in Randomized Experiments:
  Machine Learning for Variance Reduction
Estimating Distributional Treatment Effects in Randomized Experiments: Machine Learning for Variance Reduction
Undral Byambadalai
Tatsushi Oka
Shota Yasui
CML
185
6
0
22 Jul 2024
MSCT: Addressing Time-Varying Confounding with Marginal Structural
  Causal Transformer for Counterfactual Post-Crash Traffic Prediction
MSCT: Addressing Time-Varying Confounding with Marginal Structural Causal Transformer for Counterfactual Post-Crash Traffic Prediction
Shuang Li
Ziyuan Pu
Nan Zhang
Duxin Chen
Lu Dong
Daniel J. Graham
Yinhai Wang
274
0
0
19 Jul 2024
Causal Inference with Complex Treatments: A Survey
Causal Inference with Complex Treatments: A Survey
Yingrong Wang
Haoxuan Li
Minqin Zhu
Anpeng Wu
Ruoxuan Xiong
Leilei Gan
Kun Kuang
CML
189
3
0
19 Jul 2024
Decision Focused Causal Learning for Direct Counterfactual Marketing
  Optimization
Decision Focused Causal Learning for Direct Counterfactual Marketing Optimization
Hao Zhou
Rongxiao Huang
Shaoming Li
Guibin Jiang
Jiaqi Zheng
Bing Cheng
Wei Lin
236
7
0
18 Jul 2024
Model-agnostic meta-learners for estimating heterogeneous treatment effects over time
Model-agnostic meta-learners for estimating heterogeneous treatment effects over time
Dennis Frauen
Konstantin Hess
Stefan Feuerriegel
436
13
0
07 Jul 2024
Stable Heterogeneous Treatment Effect Estimation across
  Out-of-Distribution Populations
Stable Heterogeneous Treatment Effect Estimation across Out-of-Distribution Populations
Yuling Zhang
Anpeng Wu
Kun Kuang
Liang Du
Zixun Sun
Zhi Wang
OODD
275
2
0
03 Jul 2024
CausalPrism: A Visual Analytics Approach for Subgroup-based Causal
  Heterogeneity Exploration
CausalPrism: A Visual Analytics Approach for Subgroup-based Causal Heterogeneity Exploration
Jiehui Zhou
Xumeng Wang
Kam-Kwai Wong
Wei Zhang
Xingyu Liu
Juntian Zhang
Minfeng Zhu
Wei Chen
CML
224
2
0
02 Jul 2024
Proximity Matters: Local Proximity Preserved Balancing for Treatment
  Effect Estimation
Proximity Matters: Local Proximity Preserved Balancing for Treatment Effect Estimation
Hao Wang
Zhichao Chen
Yuan Shen
Jiajun Fan
Zhaoran Liu
Degui Yang
Xinggao Liu
Haoxuan Li
183
1
0
01 Jul 2024
Improve ROI with Causal Learning and Conformal Prediction
Improve ROI with Causal Learning and Conformal Prediction
Meng Ai
Zhuo Chen
Jibin Wang
Jing Shang
Tao Tao
Zhen Li
269
2
0
01 Jul 2024
Compositional Models for Estimating Causal Effects
Compositional Models for Estimating Causal Effects
Purva Pruthi
David D. Jensen
CML
439
0
0
25 Jun 2024
Sources of Gain: Decomposing Performance in Conditional Average Dose
  Response Estimation
Sources of Gain: Decomposing Performance in Conditional Average Dose Response Estimation
Christopher Bockel-Rickermann
Toon Vanderschueren
Tim Verdonck
Wouter Verbeke
CML
267
2
0
12 Jun 2024
Asymptotically Optimal Regret for Black-Box Predict-then-Optimize
Asymptotically Optimal Regret for Black-Box Predict-then-Optimize
Samuel Tan
P. Frazier
149
1
0
12 Jun 2024
Estimating Heterogeneous Treatment Effects by Combining Weak Instruments
  and Observational Data
Estimating Heterogeneous Treatment Effects by Combining Weak Instruments and Observational Data
Miruna Oprescu
Nathan Kallus
CML
233
1
0
10 Jun 2024
PairNet: Training with Observed Pairs to Estimate Individual Treatment
  Effect
PairNet: Training with Observed Pairs to Estimate Individual Treatment Effect
Lokesh Nagalapatti
Pranava Singhal
Avishek Ghosh
Sunita Sarawagi
CMLOOD
289
2
0
06 Jun 2024
Prediction-powered Generalization of Causal Inferences
Prediction-powered Generalization of Causal Inferences
Ilker Demirel
Ahmed M. Alaa
Anthony Philippakis
David Sontag
OOD
220
13
0
05 Jun 2024
Meta-Learners for Partially-Identified Treatment Effects Across Multiple
  Environments
Meta-Learners for Partially-Identified Treatment Effects Across Multiple Environments
Jonas Schweisthal
Dennis Frauen
M. Schaar
Stefan Feuerriegel
CML
277
8
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
199
0
0
04 Jun 2024
G-Transformer for Conditional Average Potential Outcome Estimation over
  Time
G-Transformer for Conditional Average Potential Outcome Estimation over Time
Konstantin Hess
Dennis Frauen
Valentyn Melnychuk
Stefan Feuerriegel
315
5
0
31 May 2024
Revisiting Counterfactual Regression through the Lens of
  Gromov-Wasserstein Information Bottleneck
Revisiting Counterfactual Regression through the Lens of Gromov-Wasserstein Information Bottleneck
Hao Yang
Zexu Sun
Hongteng Xu
Xu Chen
298
6
0
24 May 2024
Blood Glucose Control Via Pre-trained Counterfactual Invertible Neural
  Networks
Blood Glucose Control Via Pre-trained Counterfactual Invertible Neural Networks
Jingchi Jiang
Rujia Shen
Boran Wang
Yi Guan
OffRLBDL
246
1
0
23 May 2024
Conformal Counterfactual Inference under Hidden Confounding
Conformal Counterfactual Inference under Hidden Confounding
Zonghao Chen
Ruocheng Guo
Jean-François Ton
Yang Liu
CMLOffRL
458
6
0
20 May 2024
Generalization Bounds for Causal Regression: Insights, Guarantees and
  Sensitivity Analysis
Generalization Bounds for Causal Regression: Insights, Guarantees and Sensitivity AnalysisInternational Conference on Machine Learning (ICML), 2024
Daniel Csillag
C. Struchiner
G. Goedert
OODCML
234
3
0
15 May 2024
Doubly Robust Causal Effect Estimation under Networked Interference via
  Targeted Learning
Doubly Robust Causal Effect Estimation under Networked Interference via Targeted LearningInternational Conference on Machine Learning (ICML), 2024
Weilin Chen
Ruichu Cai
Zeqin Yang
Jie Qiao
Yuguang Yan
Zijian Li
Zhifeng Hao
CML
243
12
0
06 May 2024
Be Aware of the Neighborhood Effect: Modeling Selection Bias under
  Interference
Be Aware of the Neighborhood Effect: Modeling Selection Bias under Interference
Haoxuan Li
Chunyuan Zheng
Sihao Ding
Peng Wu
Zhi Geng
Fuli Feng
Xiangnan He
CML
198
12
0
30 Apr 2024
Differentiable Pareto-Smoothed Weighting for High-Dimensional
  Heterogeneous Treatment Effect Estimation
Differentiable Pareto-Smoothed Weighting for High-Dimensional Heterogeneous Treatment Effect Estimation
Yoichi Chikahara
Kansei Ushiyama
400
0
0
26 Apr 2024
Neural Networks with Causal Graph Constraints: A New Approach for
  Treatment Effects Estimation
Neural Networks with Causal Graph Constraints: A New Approach for Treatment Effects Estimation
Roger Pros
Jordi Vitrià
CML
242
0
0
18 Apr 2024
Causal Effect Estimation Using Random Hyperplane Tessellations
Causal Effect Estimation Using Random Hyperplane Tessellations
Abhishek Dalvi
Neil Ashtekar
V. Honavar
313
0
0
16 Apr 2024
C-XGBoost: A tree boosting model for causal effect estimation
C-XGBoost: A tree boosting model for causal effect estimation
Niki Kiriakidou
I. Livieris
Christos Diou
CML
165
3
0
31 Mar 2024
Uplift Modeling Under Limited Supervision
Uplift Modeling Under Limited Supervision
G. Panagopoulos
Daniele Malitesta
Fragkiskos D. Malliaros
Jun Pang
CML
344
2
0
28 Mar 2024
A Causal Analysis of CO2 Reduction Strategies in Electricity Markets
  Through Machine Learning-Driven Metalearners
A Causal Analysis of CO2 Reduction Strategies in Electricity Markets Through Machine Learning-Driven Metalearners
Iman Emtiazi Naeini
Zahra Saberi
Khadijeh Hassanzadeh
80
0
0
21 Mar 2024
Graph Machine Learning based Doubly Robust Estimator for Network Causal
  Effects
Graph Machine Learning based Doubly Robust Estimator for Network Causal Effects
Seyedeh Baharan Khatami
Harsh Parikh
Haowei Chen
Sudeepa Roy
Babak Salimi
OOD
218
4
0
17 Mar 2024
ODE Discovery for Longitudinal Heterogeneous Treatment Effects Inference
ODE Discovery for Longitudinal Heterogeneous Treatment Effects Inference
Krzysztof Kacprzyk
Samuel Holt
Jeroen Berrevoets
Zhaozhi Qian
M. Schaar
256
12
0
16 Mar 2024
Triple/Debiased Lasso for Statistical Inference of Conditional Average
  Treatment Effects
Triple/Debiased Lasso for Statistical Inference of Conditional Average Treatment Effects
Masahiro Kato
CML
286
1
0
05 Mar 2024
Pareto-Optimal Estimation and Policy Learning on Short-term and
  Long-term Treatment Effects
Pareto-Optimal Estimation and Policy Learning on Short-term and Long-term Treatment Effects
Yingrong Wang
Anpeng Wu
Haoxuan Li
Weiming Liu
Qiaowei Miao
Ruoxuan Xiong
Leilei Gan
Kun Kuang
276
0
0
05 Mar 2024
Defining Expertise: Applications to Treatment Effect Estimation
Defining Expertise: Applications to Treatment Effect Estimation
Alihan Huyuk
Qiyao Wei
Alicia Curth
M. Schaar
CML
221
3
0
01 Mar 2024
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