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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OrthoGen: A Generative Orthogonal Learner for Time-Varying Treatments
Oct 7, 2026Tomàs Garriga, Valentyn Melnychuk, Konstantin Hess +4Causal Effect Estimation Causal Inference
Novartis · Barcelona Supercomputing Center · Universitat Polit`ecnica de Catalunya +2
Policy Learning with Weak Signals
Oct 7, 2026Benedikt Koch, Winston Chou, Aurélien Bibaut +1Policy Learning Causal Effect Estimation
Harvard University · Netflix
Symmetry-Informed Causal Partial Identification
Oct 6, 2026Uzair Akbar, Zulfiqar Zaidi, Niki Kilbertus +2Causal Inference Causal Effect Estimation
Georgia Tech · TU Munich · Helmholtz Munich +2
Variance-Optimal Off-Policy Evaluation with Conjunct Effect Modeling
Oct 6, 2026Nicolò Felicioni, Michael Benigni, Maurizio Ferrari Dacrema +1Causal Effect Estimation Off-Policy Evaluation
Spotify · Politecnico di Milano
Incentive Alignment in Online Experimentation
Oct 5, 2026Ermis Soumalias, Richard Mudd, Abbas ZaidiCausal Effect Estimation A/b Testing
Meta Platforms, Inc.
Proximal Balancing for Causal Effect Estimation under Unmeasured Confounding
Sep 30, 2026Yonghan JungCausal Effect Estimation Causal Inference
School of Information Sciences University of Illinois Urbana-Champaign
Target-Dependent Limits of Causal Repair: A Leading-Log Frontier in a Gaussian Model
Sep 30, 2026Qinchuan Cheng, Jiaqi Liu, Ruixuan XieCausal Effect Estimation Causal Inference
Xi’an Jiaotong University · Sichuan University · Southwestern University of Finance and Economics
Search Shapes Conclusions: Auditing Evidence Selection Bias in Deep Research Agents
Sep 30, 2026Shuyao Xiao, Shengling Wang, Xuan Chen +8Causal Effect Estimation Deep Research Agents
Beijing Normal University · Ke Holdings
Do-JEPA: From Masking to Intervention in Latent World Models
Sep 29, 2026Hossein Resani, Javen Qinfeng ShiCausal Effect Estimation Causal World Models
Australian Institute for Machine Learning, Adelaide University · Responsible AI Research Centre
Weighted Spline-Expanded Networks with Distributional Balancing for Continuous Treatment Effects
Sep 27, 2026Shucheng Liu, Chan Park, Guanhua ChenCausal Effect Estimation Doubly Robust Estimation
University of North Carolina at Chapel Hill · University of Illinois Urbana-Champaign · University of Wisconsin–Madison
Path-specific harm decomposition: A partial identification framework
Sep 24, 2026Ruizi Yan, Dennis Frauen, Maresa Schröder +1Causal Effect Estimation Causal Mediation Analysis
Department of Statistics, University of Oxford · LMU Munich · Munich Center for Machine Learning (MCML)
A General Framework for Budgeted Threshold Incentives on Request
Sep 24, 2026Zhuolin Wu, Chengrui Zhu, Wenhua Nie +9Causal Effect Estimation Online Resource Allocation
Meituan · National Taiwan University · Tsinghua University +1
GeoDose-CP: Graph-Local Conformal Inference for Continuous-Treatment Earth Observation
Sep 24, 2026Md Khalid Hasan Sakib, Dristi Datta, Manoranjan Paul +1Weighted Conformal Prediction Causal Effect Estimation
Department of Computer Science and Engineering, Uttara University, Dhaka, Bangladesh · School of Computing, Mathematics and Engineering, Charles Sturt University, Bathurst, NSW 2795, Australia · Australian Integrated Carbon (AiCarbon), Level 4, 191 Pulteney Street, Adelaide, SA 5000, Australia
KITE: Scaling Jev Population Experiments with Sparse Flagship Calibration
Sep 23, 2026Hengyu LiCausal Effect Estimation Uncertainty Quantification
The University of Tokyo
Beyond the Illusion of Power: Calibrating Quasi-Experiments in Observational IS
Sep 23, 2026Spandan Ghose ChowdhuryCausal Effect Estimation Statistical Power Analysis
Georgia Institute of Technology, GA, USA
Artificial intelligence surrogates for treatment effect estimation with before-and-after data
Sep 23, 2026Frances Dean, Anna Neufeld, Joshua Barrios +2Surrogate Modeling Causal Effect Estimation
University of California, Berkeley · University of California, San Francisco · Williams College
Beyond Overlap: Estimating the Causal Effect of Benchmark Exposure
Sep 23, 2026Divyansh SinghCausal Effect Estimation Benchmark Design
University of Florida
Learning to Fluctuate: Statistical Foundations for Causal Tabular Pretraining
Sep 22, 2026Zhiheng ZhangCausal Foundation Models Synthetic Data Pretraining
School of Statistics and Data Science Shanghai University of Finance and Economics
Exponential Family Synthetic Controls
Sep 21, 2026Hector Rodriguez-Deniz, David M. BleiCausal Effect Estimation
Data Science Institute Columbia University New York, NY 10027, USA · Department of Computer Science and Department of Statistics Columbia University New York, NY 10027, USA
Information Set Emulation: Causal Certificates for AI Derived EHR Features
Sep 15, 2026Takes Fujita, Nobutaka HattoriCausal Effect Estimation Partial Identification
VRI · Department of Neurology, Juntendo University School of Medicine
When AI Generates Covariates: Causal Typing and Estimand Drift in Sequential Experiments
Sep 15, 2026Takes Fujita, Nobutaka HattoriCausal Effect Estimation Causal Inference
VRI · Department of Neurology, Juntendo University School of Medicine
Splitting the Difference: Interpretable Causal Forests for Treatment Effect Heterogeneity and Bias
Sep 15, 2026Nicolas Alexander Ihlo, Merle BehrCausal Effect Estimation Conditional Average Treatment Effect Estimation
Faculty of Informatics and Data Science University of Regensburg, Germany
Conformal Individual Treatment Effect Estimation under Networked Interference
Sep 14, 2026Matteo Zecchin, Osvaldo SimeoneWeighted Conformal Prediction Causal Effect Estimation
Communication Systems Department, EURECOM, Sophia Antipolis, France · Institute for Intelligent Networked Systems (INSI), Northeastern University London, London, UK
Differentially Private Average Treatment Effect Estimation by Propensity Score Blocking
Sep 8, 2026Duncan Stewardson, Grayson W. White, Adam GroceInverse Probability Weighting Causal Effect Estimation
Department of Computer Science Reed College Portland, OR, 97202 · Department of Mathematics and Statistics Reed College Portland, OR, 97202
CausalVerify: An Execution-Grounded Benchmark for LLM Causal Inference Workflows
Sep 7, 2026Yonghong Zhang, Ricardo Correia, Isabel M. Parra +1LLM Evaluation Causal Effect Estimation
Department of Finance Universidad Autónoma de Madrid Madrid, Spain · Spanish National Research Council (CSIC) Madrid, Spain
A location-invariant estimator of extremal quantile treatment effects for heavy-tailed distributions
Sep 3, 2026Xin Yu, Shuwei Huang, Jicheng Liu +4Causal Effect Estimation Heavy-Tailed Distributions
Huazhong University of Science and Technology · Tencent
Causal Foundation Models
Sep 2, 2026Christopher Stith, Hossein Rahmani, Jesse C. CresswellCausal Foundation Models Causal Effect Estimation
Layer 6 AI, Toronto, Canada · TD Bank Group, Toronto, Canada
Exploring Sparse Autoencoders in Text-Based Causal Confounding Adjustment
Sep 1, 2026Mian Zhong, Katherine A. Keith, Anjalie FieldCausal Effect Estimation Sparse Autoencoders
Johns Hopkins University · Williams College / Cohere · Cohere
When Prediction Error Is Not Enough: Evaluating Nuisance-Function Prediction for Causal Estimation
Aug 30, 2026Cong CaoSemiparametric Inference Causal Effect Estimation
Department of Biostatistics, Yale University, New Haven, CT 06520, USA
Across-Design Uncertainty in Short Pricing Panels: Inference and Identification
Aug 21, 2026Pedro Cadahia DelgadoCausal Effect Estimation Uncertainty Quantification
PhD, Universidad de Huelva, Spain

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OrthoGen: A Generative Orthogonal Learner for Time-Varying Treatments

Tomàs Garriga, Valentyn Melnychuk, Konstantin Hess, Eduard Serrahima de Cambra+3

Novartis · Barcelona Supercomputing Center · Universitat Polit`ecnica de Catalunya+2

Causal Effect Estimation Causal Inference Doubly Robust Estimation Conditional Generative Modeling

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Estimating conditional distributional potential outcomes (CDPOs) over time is important in medicine (e.g., to estimate patient-specific risks under different treatment sequences). However, this task is challenging because of time-varying confounding, yet existing adjustment strategies for this task are limited. In this paper, we aim to learn CDPOs under time-varying treatments using flexible generative models. Our contributions are two-fold. (1) We introduce a tailored adjustment strategy for our setting, namely, generative recursive g-computation. Our adjustment strategy recursively propagates full conditional outcome distributions rather than conditional means, modeling the variables of interest directly rather than full trajectories. Building on our adjustment strategy, we formulate simple generative learners for CDPO estimation. However, these learners can be sensitive to nuisance estimation errors, which motivates an orthogonal learner. (2) We thus introduce OrthoGen, a Neyman-orthogonal and doubly robust generative learner. Importantly, we show that OrthoGen further achieves rate double robustness and quasi-oracle efficiency under suitable conditions. Our learners are flexible and can be instantiated with different generative backbones (e.g., normalizing flows and diffusion models). Across experiments with synthetic, semi-synthetic and real-world datasets, we find that OrthoGen is highly effective. To the best of our knowledge, we are the first to propose a generative orthogonal learner for estimating CDPOs under time-varying treatments.

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