Causal Effect Estimation

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20 papers in the last four weeks, up 100% on the four weeks before. 0.2% of all new papers.

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Adaptive Experimentation for Censored Survival Outcomes
May 18, 2026Yuxin Wang, Dennis Frauen, Jonas Schweisthal +3Causal Effect Estimation Survival Analysis
LMU Munich Munich Center of Machine Learning (MCML)
Decision-Aware Proximal Bridge Learning for Optimal Treatment Selection
May 16, 2026Tomàs Garriga, Alejandro Almodóvar, Axel Brando +3Causal Effect Estimation Decision-Focused Learning
1Novartis · 2Barcelona Supercomputing Center · 3Universidad Politécnica de Madrid
From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction
May 16, 2026Pujun Feng, Xiaoyu Guo, Seyed Ehsan Saffari +10Causal Effect Estimation Off-Policy Evaluation
Faculty of Applied Sciences, Macao Polytechnic University, Macao SAR 999078, China. · Medin.ai, Beijing 100871, China. · School of Software & Microelectronics, Peking University, Beijing 100871, China. +8
Causal Foundation Models with Continuous Treatments
May 14, 2026Christopher Stith, Medha Barath, Vahid Balazadeh +2Causal Foundation Models Causal Effect Estimation
Layer 6 AI · University of Toronto · Vector Institute
Smooth Multi-Policy Causal Effect Estimation in Longitudinal Settings
May 14, 2026Wenxin Chen, Weishen Pan, Kyra Gan +1Causal Effect Estimation Causal Inference
Cornell University, New York, US.
Towards a holistic understanding of Selection Bias for Causal Effect Identification
May 13, 2026Yiwen Qiu, Filip Kovačević, Shimeng Huang +2Causal Effect Estimation Data Selection
Institute of Science and Technology Austria (ISTA) · Carnegie Mellon University
IV-ICL: Bounding Causal Effects with Instrumental Variables via In-Context Learning
May 13, 2026Vahid Balazadeh, Hamidreza Kamkari, Medha Barath +2Causal Effect Estimation Parameter Identifiability
University of Toronto · Vector Institute · MIT CSAIL +1
Robust Sequential Experimental Design for A/B Testing
May 13, 2026Qianglin Wen, Xiangkun Wu, Chengchun Shi +4Causal Effect Estimation Model Misspecification
Yunnan Key Laboratory of Statistical Modeling and Data Analysis, Yunnan University, Kunming, China · School of Mathematical Sciences, Zhejiang University, Hangzhou, China · Department of Statistics, London School of Economics and Political Science, London, United Kingdom +3
Digital Twins as Synthetic Controls in Single-Arm Trials
May 12, 2026Daniele Bertolini, Franklin Fuller, Aaron M. Smith +2Causal Effect Estimation Digital Twins
Unlearn.AI, Inc., San Francisco, CA
Learning plug-in surrogate endpoints for randomized experiments
May 12, 2026Alessandro-Umberto Margueritte, Ahmet Zahid Balcıoğlu, Jesse Krijthe +2Causal Effect Estimation
AstraZeneca · Chalmers University of Technology and University of Gothenburg · TU Delft +1
Causal Algorithmic Recourse: Foundations and Methods
May 12, 2026Drago Plecko, Collin Wang, Elias BareinboimCopula Models Causal Effect Estimation
Department of Statistics & Data Science UCLA Los Angeles, CA 90095, USA · Department of Computer Science Columbia University New York, NY 10027, USA
Amortizing Causal Sensitivity Analysis via Prior Data-Fitted Networks
May 11, 2026Emil Javurek, Dennis Frauen, Marie Brockschmidt +2Causal Effect Estimation Amortized Inference
1LMU Munich · 2Munich Center for Machine Learning (MCML)
Real vs. Semi-Simulated: Rethinking Evaluation for Treatment Effect Estimation
May 11, 2026George PanagopoulosCounterfactual Evaluation Causal Effect Estimation
Department of Computer Science University of Luxembourg 2 Av. de l’Universite, 4365 Belval Esch-sur-Alzette
Extended Wasserstein-GAN Approach to Causal Distribution Learning: Density-Free Estimation and Minimax Optimality
May 11, 2026Shu Tamano, Masaaki ImaizumiCausal Effect Estimation Causal Counterfactual Generation
1The University of Tokyo · 2Japan Institute for Health Security · 3RIKEN Center for Advanced Intelligence Project +1
Doubly Robust Proxy Causal Learning with Neural Mean Embeddings
May 10, 2026Bariscan Bozkurt, Alexandre Galashov, Dimitri Meunier +3Causal Effect Estimation Causal Inference
University College London
Sinkhorn Treatment Effects: A Causal Optimal Transport Measure
May 8, 2026Medha Agarwal, Alex LuedtkeCausal Effect Estimation Causal Inference
Department of Statistics, University of Washington, Seattle, WA, USA · Department of Health Care Policy, Harvard Medical School, Boston, MA, USA
Semiparametric Efficient Test for Interpretable Distributional Treatment Effects
May 8, 2026Houssam Zenati, Arthur GrettonSemiparametric Inference Causal Effect Estimation
1Gatsby Computational Neuroscience Unit, University College London
Bayesian Sensitivity of Causal Inference Estimators under Evidence-Based Priors
May 8, 2026Nikita Dhawan, Daniel Shen, Leonardo Cotta +1Causal Effect Estimation Bayesian Inference
University of Toronto Vector Institute · University of Waterloo · Vector Institute
Three-in-One World Model: Energy-Based Consistency, Prediction, and Counterfactual Inference for Marketing Intervention
May 8, 2026Junichiro NiimiCausal Effect Estimation World Model Learning
1Meijo University
Causal EpiNets: Precision-corrected Bounds on Individual Treatment Effects using Epistemic Neural Networks
May 8, 2026Gandharv Patil, Keyi Tang, Raquel Aoki +1Causal Effect Estimation Causal Identifiability
McGill University/Mila · RBC Borealis
BGM-IV: AI-Powered Bayesian Generative Modeling for Instrumental Variable Regression with High-Dimensional Covariates
May 7, 2026Guyue Luo, Haidong Lu, Andrew J. Loza +1Causal Effect Estimation Latent Variable Models
Department of Biostatistics Yale University
Optimal Experiments for Partial Causal Effect Identification
May 7, 2026Tobias Maringgele, Jalal EtesamiCausal Effect Estimation Partial Identification
Technical University of Munich · UC Berkeley
DARTS: Targeting Prognostic Covariates in Budget-Constrained Sequential Experiments
May 7, 2026Kateryna Husar, Alexander VolfovskyThompson Sampling Causal Effect Estimation
Department of Statistical Science Duke University Durham, NC 27705
Covariate Balancing and Riesz Regression Should Be Guided by the Neyman Orthogonal Score in Debiased Machine Learning
May 7, 2026Masahiro KatoCausal Effect Estimation Debiased ML
Data Analytics Department, Mizuho-DL Financial Technology, Co., Ltd.
Data-Driven Covariate Selection for Nonparametric and Cycle-Agnostic Causal Effect Estimation
May 7, 2026Ana Leticia Garcez Vicente, Gijs van Seeventer, Saber SalehkaleybarCausal Effect Estimation Structural Causal Models
Leiden University Netherlands
TabCF: Distributional Control Function Estimation with Tabular Foundation Models
May 7, 2026Geping Chen, Chunlin Li, Tianzhong Yang +2Causal Effect Estimation Instrumental Variable Estimation
Iowa State University · University of Virginia · University of Minnesota +1
RepFlow: Representation Enhanced Flow Matching for Causal Effect Estimation
May 7, 2026Yifei Xie, Jian HuangCausal Effect Estimation Causal Representation Learning
Department of Data Science and Artificial Intelligence, The Hong Kong Polytechnic University, Hong Kong, China.
Resolving the bias-precision paradox with stochastic causal representation learning for personalized medicine
May 7, 2026Peisong Zhang, Manqiang Peng, Yuxuan Wu +21Causal Effect Estimation Causal Representation Learning
School of Medicine, NUS, . · College of Design and Engineering, NUS, . · Aier Academy of Ophthalmology, Central South University. +14
Joint Treatment Effect Estimation from Incomplete Healthcare Data: Temporal Causal Normalizing Flows with LLM-driven Evolutionary MNAR Imputation
May 6, 2026Olivia Jullian Parra, Sara Zoccheddu, David Catalan Cerezo +7Causal Effect Estimation Normalizing Flows
Department of Mathematical Modeling and Machine Learning University of Zürich Winterthurerstrasse 190, Zürich 8057 · Department of Mathematics ETH Zürich Rämistrasse 101, Zürich 8092 · Epidemiology, Biostatistics & Prevention Institute (EBPI), University of Zürich Hirschengraben 84, Zürich 8001 +2
Regime-Conditioned Evaluation in Multi-Context Bayesian Optimization
May 6, 2026Noel ThomasCausal Effect Estimation Conditional Average Treatment Effect Estimation
Mohamed bin Zayed University of Artificial Intelligence Abu Dhabi, UAE

May 18, 2026, cs.LGJ/K move · Enter open · S save

Adaptive Experimentation for Censored Survival Outcomes

Yuxin Wang, Dennis Frauen, Jonas Schweisthal, Maresa Schröder+2

LMU Munich Munich Center of Machine Learning (MCML)

Causal Effect Estimation Survival Analysis

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Adaptive experimentation enables efficient estimation of causal effects, but existing methods are not designed for survival data with censoring, where event times are only partially observed (e.g., overall survival in cancer trials but with dropout). In this paper, we develop a novel framework for adaptive experimentation to estimate causal effects under right censoring. For this, we derive the semiparametric efficiency bound for the average survival effect curve as a function of the treatment allocation policy and thereby obtain a closed-form efficiency-optimal allocation policy. The policy generalizes classical Neyman allocation to survival settings by prioritizing patient strata where both event and censoring dynamics induce high uncertainty. Building on this, we propose the Adaptive Survival Estimator (ASE), an adaptive framework that learns the allocation policy and estimates the average survival effect curve sequentially. Our framework has three main benefits: (i) it accommodates arbitrary machine learning models for nuisance estimation; (ii) it is guided by a closed-form efficiency-optimal allocation policy; and (iii) it admits strong theoretical guarantees, including asymptotic normality via a martingale central limit theorem. We demonstrate our framework across various numerical experiments to show consistent efficiency gains over uniform randomization and censoring-agnostic baselines.

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