Causal Inference

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21 papers in the last four weeks, up 62% on the four weeks before. 0.2% of all new papers.

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Latest papers 222

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From Baseline to Follow-Up: Counterfactual Spine DXA Image Synthesis in UK Biobank Using a Causal Hierarchical Variational Autoencoder
May 21, 2026Yilin Zhang, Nicholas C. Harvey, Nicholas R. Fuggle +1Medical Imaging Image Generation
School of Electronics and Computer Science University of Southampton Southampton, UK · MRC Lifecourse Epidemiology Centre University of Southampton, Southampton General Hospital Southampton, UK
Robust Personalized Recommendation under Hidden Confounding in MNAR
May 20, 2026Zongyu Li, Wanting Su, Tianyu XiaRecommender Systems Causal Inference
Guangdong University of Technology · Guangzhou, China · Chinese Academy of Sciences +3
Local Covariate Selection for Average Causal Effect Estimation without Pretreatment and Causal Sufficiency Assumptions
May 20, 2026Zeyu Liu, Zheng Li, Feng Xie +3Causal Effect Estimation Causal Discovery
Department of Applied Statistics, Beijing Technology and Business University, Beijing, China · Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China · College of Computer Science and Artificial Intelligence, Fudan University, Shanghai, China +2
Causal Machine Learning Is Not a Panacea: A Roadmap for Observational Causal Inference in Health
May 20, 2026Donna Tjandra, Trenton Chang, Sonali Parbhoo +8Healthcare Causal Inference
Division of Computer Science and Engineering, University of Michigan, Ann Arbor, Michigan, United States · Department of Electrical and Electronic Engineering, Imperial College London, London, UK · Courant Institute of Mathematical Sciences, New York University, New York, New York, United States +8
The Illusion of Intervention: Your LLM-Simulated Experiment is an Observational Study
May 20, 2026Victoria Lin, Taedong Yun, Maja Matarić +3Human Behavior Simulation Large Language Model-Based Social Simulation
Google DeepMind · Carnegie Mellon University
CasualSynth: Generating Structurally Sound Synthetic Data
May 17, 2026Zehua Cheng, Wei Dai, Jiahao Sun +1Structural Causal Models Synthetic Data Generation
Department of Computer Science, University of Oxford · FLock.io United Kingdom · Institute of Logic and Computation, TU Wien
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
Prediction-Intervention Games and Invariant Sets
May 16, 2026Linus Kühne, Felix Schur, Jonas PetersStructural Causal Models Game Theory
Seminar for Statistics and ETH AI Center · ETH Zurich · Zurich, Switzerland +1
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.
Causal Learning with the Invariance Principle
May 13, 2026Francesco Montagna, Francesco LocatelloStructural Causal Models Causal Discovery
Institute of Science and Technology Austria
A General Bézier Tree Encoding Counterfactual Framework for Retinal-Vessel-Mediated Disease Analysis
May 13, 2026Tan Su, Ethan Elio Meidinger, Lin Gu +1Medical Image Analysis Causal Counterfactual Generation
Department of Electronic and Electrical Engineering, Southern University of Science and Technology · School of Data Science,University of Virginia, Charlottesville · Research Institute of Electrical Communication, Tohoku University +1
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
PROMETHEUS: Automating Deep Causal Research Integrating Text, Data and Models
May 13, 2026Sridhar MahadevanCausal World Models Causal Attribution
Adobe Research · University of Massachusetts, Amherst
Controllable User Simulation
May 12, 2026Guy Tennenholtz, Ofer Meshi, Amir Globerson +3Off-Policy Evaluation Causal Inference
† Google Research · ‡ Tel Aviv University
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
Causal Bias Detection in Generative Artificial Intelligence
May 12, 2026Drago PleckoAlgorithmic Fairness Language Model Bias Evaluation
Department of Statistics & Data Science UCLA
Causal Fairness for Survival Analysis
May 12, 2026Drago PleckoCausal Mediation Analysis Survival Analysis
Department of Statistics & Data Science UCLA
An Uncertainty-Aware Resilience Micro-Agent for Causal Observability in the Computing Continuum
May 11, 2026Suvi De Silva, Alfreds Lapkovskis, Alaa Saleh +2Agent Reliability Edge Computing
Department of Computer Systems and Sciences, Stockholm University, Stockholm 164 25, Sweden · Department of Computer Science, University of Helsinki, Helsinki 00014, Finland
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)
ConfoundingSHAP: Quantifying confounding strength in causal inference
May 11, 2026Marie Brockschmidt, Santo M. A. R. Thies, Maresa Schröder +5Shapley Value Attribution Causal Inference
LMU Munich · Munich Center for Machine Learning (MCML) · German Research Center for Artificial Intelligence (DFKI)
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
Debiased Counterfactual Generation via Flow Matching from Observations
May 8, 2026Hugh Dance, Johnny Xi, Peter Orbanz +1Flow Matching Causal Counterfactual Generation
Gatsby Computational Neuroscience Unit University College London · Department of Statistics University of British Columbia
Mathematical Reasoning via Intervention-Based Time-Series Causal Discovery Using LLMs as Concept Mastery Simulators
May 8, 2026Tsuyoshi OkitaMathematical Reasoning Causal Inference
Kyushu Institute of Technology
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

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From Baseline to Follow-Up: Counterfactual Spine DXA Image Synthesis in UK Biobank Using a Causal Hierarchical Variational Autoencoder

Yilin Zhang, Nicholas C. Harvey, Nicholas R. Fuggle, Rahman Attar

School of Electronics and Computer Science University of Southampton Southampton, UK · MRC Lifecourse Epidemiology Centre University of Southampton, Southampton General Hospital Southampton, UK

Medical Imaging Image Generation Medical Image Synthesis Causal Inference Conditional Variational Autoencoder

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Dual-energy X-ray absorptiometry (DXA) is widely used for large-scale skeletal assessment, yet learning controllable and interpretable factor-specific anatomical variation remains challenging. We propose a metadata-conditioned causal hierarchical variational autoencoder (CHVAE) for causally consistent generation of anteroposterior (AP) spine DXA images from the UK Biobank (UKB). The model is trained on 3,743 raw AP spine scans from the first imaging visit and conditioned on basic participant attributes and lumbar morphometry. Causal consistency is evaluated in a baseline-to-follow-up setting using abduction--action--prediction (AAP): latent variables are abducted from baseline images, age is intervened to the repeat-imaging value, and the resulting counterfactual follow-up morphometry is compared with observed repeat-imaging measurements. Results show strong absolute-level agreement for key vertebral morphometry variables under age intervention, supporting intervention-aligned synthesis of anatomically plausible DXA images.

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