{"total":53,"rows":[{"id":"2410.08770","title":"Causal machine learning for predicting treatment outcomes","created":"2024-10-11","cited_by_count":74,"area":null},{"id":"2310.17463","title":"Bayesian Neural Controlled Differential Equations for Treatment Effect Estimation","created":"2023-10-26","cited_by_count":26,"area":null},{"id":"2311.11321","title":"Bounds on Representation-Induced Confounding Bias for Treatment Effect Estimation","created":"2023-11-19","cited_by_count":20,"area":null},{"id":"2407.05287","title":"Model-agnostic meta-learners for estimating heterogeneous treatment effects over time","created":"2024-07-07","cited_by_count":19,"area":null},{"id":"2303.02320","title":"Estimating Treatment Effects from Irregular Time Series Observations with Hidden Confounders","created":"2023-03-04","cited_by_count":17,"area":null},{"id":"2305.15742","title":"Counterfactual Generative Models for Time-Varying Treatments","created":"2023-05-25","cited_by_count":17,"area":null},{"id":"2306.11216","title":"CF-GODE: Continuous-Time Causal Inference for Multi-Agent Dynamical Systems","created":"2023-06-20","cited_by_count":16,"area":null},{"id":"2405.20799","title":"Rough Transformers: Lightweight and Continuous Time Series Modelling through Signature Patching","created":"2024-05-31","cited_by_count":16,"area":null},{"id":"2306.04255","title":"Accounting For Informative Sampling When Learning to Forecast Treatment Outcomes Over Time","created":"2023-06-07","cited_by_count":15,"area":null},{"id":"2410.23691","title":"Automatically Learning Hybrid Digital Twins of Dynamical Systems","created":"2024-10-31","cited_by_count":14,"area":null},{"id":"2403.10766","title":"ODE Discovery for Longitudinal Heterogeneous Treatment Effects Inference","created":"2024-03-16","cited_by_count":12,"area":null},{"id":"2209.08860","title":"A Survey of Deep Causal Models and Their Industrial Applications","created":"2022-09-19","cited_by_count":10,"area":null},{"id":"2405.21012","title":"IGC-Net for conditional average potential outcome estimation over time","created":"2024-05-31","cited_by_count":10,"area":null},{"id":"2210.10530","title":"Adversarial De-confounding in Individualised Treatment Effects Estimation","created":"2022-10-19","cited_by_count":9,"area":null},{"id":"2403.00178","title":"Causal Graph ODE: Continuous Treatment Effect Modeling in Multi-agent Dynamical Systems","created":"2024-02-29","cited_by_count":8,"area":null},{"id":"2406.05504","title":"G-Transformer: Counterfactual Outcome Prediction under Dynamic and Time-varying Treatment Regimes","created":"2024-06-08","cited_by_count":8,"area":null},{"id":"2406.00535","title":"Causal Contrastive Learning for Counterfactual Regression Over Time","created":"2024-06-01","cited_by_count":7,"area":null},{"id":"2410.03514","title":"Stabilized Neural Prediction of Potential Outcomes in Continuous Time","created":"2024-10-04","cited_by_count":7,"area":null},{"id":"2403.10288","title":"Rough Transformers for Continuous and Efficient Time-Series Modelling","created":"2024-03-15","cited_by_count":6,"area":null},{"id":"2406.06149","title":"Decoupled Marked Temporal Point Process using Neural Ordinary Differential Equations","created":"2024-06-10","cited_by_count":6,"area":null},{"id":"2502.05295","title":"GST-UNet: A Neural Framework for Spatiotemporal Causal Inference with Time-Varying Confounding","created":"2025-02-07","cited_by_count":5,"area":null},{"id":"2410.10174","title":"Balanced Neural ODEs: nonlinear model order reduction and Koopman operator approximations","created":"2024-10-14","cited_by_count":4,"area":null},{"id":"2506.21154","title":"Transformer-Based Spatial-Temporal Counterfactual Outcomes Estimation","created":"2025-06-26","cited_by_count":4,"area":null},{"id":"2508.00657","title":"TrajSurv: Learning Continuous Latent Trajectories from Electronic Health Records for Trustworthy Survival Prediction","created":"2025-08-01","cited_by_count":4,"area":null},{"id":"2508.13355","title":"Counterfactual Probabilistic Diffusion with Expert Models","created":"2025-08-18","cited_by_count":4,"area":null},{"id":"2305.16791","title":"On the Generalization and Approximation Capacities of Neural Controlled Differential Equations","created":"2023-05-26","cited_by_count":3,"area":null},{"id":"2410.08816","title":"Uncertainty-Aware Optimal Treatment Selection for Clinical Time Series","created":"2024-10-11","cited_by_count":3,"area":null},{"id":"2510.19643","title":"Overlap-weighted orthogonal meta-learner for treatment effect estimation over time","created":"2025-10-22","cited_by_count":3,"area":null},{"id":"2209.04142","title":"Causal Modeling of Policy Interventions From Sequences of Treatments and Outcomes","created":"2022-09-09","cited_by_count":2,"area":null},{"id":"2302.07854","title":"Benchmarking Continuous Time Models for Predicting Multiple Sclerosis Progression","created":"2023-02-15","cited_by_count":2,"area":null},{"id":"2308.09735","title":"CTP:A Causal Interpretable Model for Non-Communicable Disease Progression Prediction","created":"2023-08-18","cited_by_count":2,"area":null},{"id":"2311.00886","title":"COSTAR: Improved Temporal Counterfactual Estimation with Self-Supervised Learning","created":"2023-11-01","cited_by_count":2,"area":null},{"id":"2511.14545","title":"DeepBlip: Estimating Conditional Average Treatment Effects Over Time","created":"2025-11-18","cited_by_count":2,"area":null},{"id":"2607.08793","title":"EHR-MPC: Inference-Time Control for Sepsis Treatment with Generative Patient Digital Twins","created":"2026-07-07","cited_by_count":2,"area":null},{"id":"2306.09656","title":"Temporal Causal Mediation through a Point Process: Direct and Indirect Effects of Healthcare Interventions","created":"2023-06-16","cited_by_count":1,"area":null},{"id":"2308.11819","title":"A Counterfactual Fair Model for Longitudinal Electronic Health Records via Deconfounder","created":"2023-08-22","cited_by_count":1,"area":null},{"id":"2311.16195","title":"A Foundational Framework and Methodology for Personalized Early and Timely Diagnosis","created":"2023-11-26","cited_by_count":1,"area":null},{"id":"2507.07271","title":"Beyond the ATE: Interpretable Modelling of Treatment Effects over Dose and Time","created":"2025-07-09","cited_by_count":1,"area":null},{"id":"2603.16789","title":"Conservative Continuous-Time Treatment Optimization","created":"2026-03-17","cited_by_count":1,"area":null},{"id":"2311.07797","title":"Explainable History Distillation by Marked Temporal Point Process","created":"2023-11-13","cited_by_count":0,"area":null},{"id":"2407.01875","title":"Spatio-Temporal Graphical Counterfactuals: An Overview","created":"2024-07-02","cited_by_count":0,"area":null},{"id":"2503.15890","title":"Time After Time: Deep-Q Effect Estimation for Interventions on When and What to do","created":"2025-03-20","cited_by_count":0,"area":null},{"id":"2509.26429","title":"An Orthogonal Learner for Individualized Outcomes in Markov Decision Processes","created":"2025-09-30","cited_by_count":0,"area":null},{"id":"2511.06189","title":"Counterfactual Forecasting for Panel Data","created":"2025-11-09","cited_by_count":0,"area":null},{"id":"2511.16427","title":"Generative Modeling of Clinical Time Series via Latent Stochastic Differential Equations","created":"2025-11-20","cited_by_count":0,"area":null},{"id":"2602.04611","title":"Targeted Synthetic Control Method","created":"2026-02-04","cited_by_count":0,"area":null},{"id":"2604.26070","title":"Observable Neural ODEs for Identifiable Causal Forecasting in Continuous Time","created":"2026-04-28","cited_by_count":0,"area":null},{"id":"2605.14284","title":"Smooth Multi-Policy Causal Effect Estimation in Longitudinal Settings","created":"2026-05-14","cited_by_count":0,"area":null},{"id":"2605.16927","title":"From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction","created":"2026-05-16","cited_by_count":0,"area":null},{"id":"2605.30213","title":"Faithful Embeddings of Irregular and Asynchronous Data for Online Log-NCDEs","created":"2026-05-28","cited_by_count":0,"area":null},{"id":"2606.05692","title":"Benchmarking Counterfactual Prediction in Epidemic Time Series with Time-Varying Interventions","created":"2026-06-04","cited_by_count":0,"area":null},{"id":"2606.19145","title":"OrthoReg: Orthogonal Regularization for Hybrid Symbolic-Neural Dynamical Systems","created":"2026-06-17","cited_by_count":0,"area":null},{"id":"2607.27224","title":"Psych-ECA: A Reproducible Semi-Synthetic Benchmark for Synthetic Control Arms in Longitudinal Psychiatry","created":"2026-07-07","cited_by_count":0,"area":null}],"next_cursor":null}