{"total":123,"rows":[{"id":"2410.08770","title":"Causal machine learning for predicting treatment outcomes","created":"2024-10-11","cited_by_count":74,"area":null},{"id":"2310.14735","title":"Unleashing the potential of prompt engineering for large language models","created":"2023-10-23","cited_by_count":72,"area":null},{"id":"2312.11598","title":"SkillDiffuser: Interpretable Hierarchical Planning via Skill Abstractions in Diffusion-Based Task Execution","created":"2023-12-18","cited_by_count":70,"area":"diffusion"},{"id":"2506.10914","title":"Foundation Models for Causal Inference via Prior-Data Fitted Networks","created":"2025-06-12","cited_by_count":32,"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":"2305.16988","title":"Sharp Bounds for Generalized Causal Sensitivity Analysis","created":"2023-05-26","cited_by_count":24,"area":null},{"id":"2303.02186","title":"Causal Deep Learning","created":"2023-03-03","cited_by_count":20,"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":"2208.08544","title":"Estimating individual treatment effects under unobserved confounding using binary instruments","created":"2022-08-17","cited_by_count":18,"area":null},{"id":"2305.15742","title":"Counterfactual Generative Models for Time-Varying Treatments","created":"2023-05-25","cited_by_count":17,"area":null},{"id":"2310.00809","title":"Towards Causal Foundation Model: on Duality between Causal Inference and Attention","created":"2023-10-01","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":"2305.19742","title":"Reliable Off-Policy Learning for Dosage Combinations","created":"2023-05-31","cited_by_count":15,"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":"2305.14406","title":"Deep Learning based Forecasting: a case study from the online fashion industry","created":"2023-05-23","cited_by_count":12,"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":"2211.03374","title":"Deep Causal Learning: Representation, Discovery and Inference","created":"2022-11-07","cited_by_count":11,"area":null},{"id":"2303.08516","title":"Fair Off-Policy Learning from Observational Data","created":"2023-03-15","cited_by_count":11,"area":null},{"id":"2304.07920","title":"Causal Decision Transformer for Recommender Systems via Offline Reinforcement Learning","created":"2023-04-17","cited_by_count":11,"area":"offlinerl"},{"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":"2312.07175","title":"Instrumental Variable Estimation for Causal Inference in Longitudinal Data with Time-Dependent Latent Confounders","created":"2023-12-12","cited_by_count":10,"area":null},{"id":"2404.04399","title":"Longitudinal Targeted Minimum Loss-based Estimation with Temporal-Difference Heterogeneous Transformer","created":"2024-04-05","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":"2302.00612","title":"Clinical Decision Transformer: Intended Treatment Recommendation through Goal Prompting","created":"2023-02-01","cited_by_count":8,"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":"2505.13092","title":"Treatment Effect Estimation for Optimal Decision-Making","created":"2025-05-19","cited_by_count":8,"area":null},{"id":"2506.09272","title":"G-Sim: Generative Simulations with Large Language Models and Gradient-Free Calibration","created":"2025-06-10","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":"2410.06392","title":"Counterfactual Causal Inference in Natural Language with Large Language Models","created":"2024-10-08","cited_by_count":7,"area":null},{"id":"2603.11090","title":"Interventional Time Series Priors for Causal Foundation Models","created":"2026-03-11","cited_by_count":7,"area":null},{"id":"2302.00293","title":"A Survey of Methods, Challenges and Perspectives in Causality","created":"2023-02-01","cited_by_count":6,"area":null},{"id":"2312.05974","title":"Learning the Causal Structure of Networked Dynamical Systems under Latent Nodes and Structured Noise","created":"2023-12-10","cited_by_count":6,"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":"2412.11511","title":"Constructing Confidence Intervals for Average Treatment Effects from Multiple Datasets","created":"2024-12-16","cited_by_count":6,"area":null},{"id":"2209.11497","title":"Time Series Causal Link Estimation under Hidden Confounding using Knockoff Interventions","created":"2022-09-23","cited_by_count":5,"area":null},{"id":"2408.07569","title":"Multi-task Heterogeneous Graph Learning on Electronic Health Records","created":"2024-08-14","cited_by_count":5,"area":null},{"id":"2501.06366","title":"Counterfactually Fair Reinforcement Learning via Sequential Data Preprocessing","created":"2025-01-10","cited_by_count":5,"area":"deeprl"},{"id":"2502.04274","title":"Orthogonal Representation Learning for Estimating Causal Quantities","created":"2025-02-06","cited_by_count":5,"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":"2207.09139","title":"Heterogeneous Treatment Effect with Trained Kernels of the Nadaraya-Watson Regression","created":"2022-07-19","cited_by_count":4,"area":null},{"id":"2303.11938","title":"3D-CLFusion: Fast Text-to-3D Rendering with Contrastive Latent Diffusion","created":"2023-03-21","cited_by_count":4,"area":"diffusion"},{"id":"2506.14329","title":"Adjustment for Confounding using Pre-Trained Representations","created":"2025-06-17","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":"2508.13355","title":"Counterfactual Probabilistic Diffusion with Expert Models","created":"2025-08-18","cited_by_count":4,"area":null},{"id":"2607.25242","title":"Medical world models in healthcare: foundations, applications, and challenges for trustworthy clinical translation","created":"2026-07-28","cited_by_count":4,"area":"wm"},{"id":"2304.07877","title":"A Neural Network Transformer Model for Composite Microstructure Homogenization","created":"2023-04-16","cited_by_count":3,"area":null},{"id":"2402.02636","title":"Can Large Language Models Learn Independent Causal Mechanisms?","created":"2024-02-04","cited_by_count":3,"area":"lr"},{"id":"2404.03804","title":"TransformerLSR: Attentive Joint Model of Longitudinal Data, Survival, and Recurrent Events with Concurrent Latent Structure","created":"2024-04-04","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":"2412.04799","title":"Estimating the treatment effect over time under general interference through deep learner integrated TMLE","created":"2024-12-06","cited_by_count":3,"area":null},{"id":"2505.16051","title":"Flow-based Generative Modeling of Potential Outcomes and Counterfactuals","created":"2025-05-21","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":"2603.05396","title":"Harnessing Synthetic Data from Generative AI for Statistical Inference","created":"2026-03-05","cited_by_count":3,"area":null},{"id":"2207.04208","title":"SCouT: Synthetic Counterfactuals via Spatiotemporal Transformers for Actionable Healthcare","created":"2022-07-09","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":"2312.15282","title":"Causal Forecasting for Pricing","created":"2023-12-23","cited_by_count":2,"area":null},{"id":"2408.08815","title":"An Empirical Examination of Balancing Strategy for Counterfactual Estimation on Time Series","created":"2024-08-16","cited_by_count":2,"area":null},{"id":"2410.10044","title":"DAG-aware Transformer for Causal Effect Estimation","created":"2024-10-13","cited_by_count":2,"area":null},{"id":"2411.00126","title":"Training and Evaluating Causal Forecasting Models for Time-Series","created":"2024-10-31","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":"2511.20558","title":"Spatio-Temporal Hierarchical Causal Models","created":"2025-11-25","cited_by_count":2,"area":null},{"id":"2210.15417","title":"Dynamic Survival Transformers for Causal Inference with Electronic Health Records","created":"2022-10-25","cited_by_count":1,"area":null},{"id":"2211.10793","title":"BENK: The Beran Estimator with Neural Kernels for Estimating the Heterogeneous Treatment Effect","created":"2022-11-19","cited_by_count":1,"area":null},{"id":"2306.05751","title":"Advancing Counterfactual Inference through Nonlinear Quantile Regression","created":"2023-06-09","cited_by_count":1,"area":null},{"id":"2310.10559","title":"Causal Dynamic Variational Autoencoder for Counterfactual Regression in Longitudinal Data","created":"2023-10-16","cited_by_count":1,"area":null},{"id":"2407.05625","title":"New User Event Prediction Through the Lens of Causal Inference","created":"2024-07-08","cited_by_count":1,"area":null},{"id":"2505.09114","title":"Beyond the Known: Decision Making with Counterfactual Reasoning Decision Transformer","created":"2025-05-14","cited_by_count":1,"area":"offlinerl"},{"id":"2506.06649","title":"SAFER: A Calibrated Risk-Aware Multimodal Recommendation Model for Dynamic Treatment Regimes","created":"2025-06-07","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":"2507.13920","title":"Causal Process Models: Reframing Dynamic Causal Graph Discovery as a Reinforcement Learning Problem","created":"2025-07-18","cited_by_count":1,"area":"deeprl"},{"id":"2602.18008","title":"Are LLMs Ready for Neural-integrated Mechanistic Modeling? A Benchmark and Agentic Framework","created":"2026-02-20","cited_by_count":1,"area":"agents"},{"id":"2603.11565","title":"CAETC: Causal Autoencoding and Treatment Conditioning for Counterfactual Estimation over Time","created":"2026-03-12","cited_by_count":1,"area":null},{"id":"2604.12992","title":"Causal Diffusion Models for Counterfactual Outcome Distributions in Longitudinal Data","created":"2026-04-14","cited_by_count":1,"area":"diffusion"},{"id":"2605.05125","title":"Joint Treatment Effect Estimation from Incomplete Healthcare Data: Temporal Causal Normalizing Flows with LLM-driven Evolutionary MNAR Imputation","created":"2026-05-06","cited_by_count":1,"area":null},{"id":"2605.14422","title":"What if Tomorrow is the World Cup Final? Counterfactual Time Series Forecasting with Textual Conditions","created":"2026-05-14","cited_by_count":1,"area":null},{"id":"2606.05797","title":"Causal Longitudinal Prior-Fitted Networks for Counterfactual Outcome Prediction","created":"2026-06-04","cited_by_count":1,"area":null},{"id":"2211.01189","title":"Inference and Denoise: Causal Inference-based Neural Speech Enhancement","created":"2022-11-02","cited_by_count":0,"area":null},{"id":"2402.04668","title":"A Perspective on Individualized Treatment Effects Estimation from Time-series Health Data","created":"2024-02-07","cited_by_count":0,"area":null},{"id":"2407.14065","title":"MSCT: Addressing Time-Varying Confounding with Marginal Structural Causal Transformer for Counterfactual Post-Crash Traffic Prediction","created":"2024-07-19","cited_by_count":0,"area":null},{"id":"2407.21185","title":"Amelia: A Large Dataset and Benchmark for Airport Surface Movement Forecasting","created":"2024-07-30","cited_by_count":0,"area":null},{"id":"2410.05177","title":"Are causal effect estimations enough for optimal recommendations under multitreatment scenarios?","created":"2024-10-07","cited_by_count":0,"area":null},{"id":"2410.14485","title":"CaTs and DAGs: Integrating Directed Acyclic Graphs with Transformers for Causally Constrained Predictions","created":"2024-10-18","cited_by_count":0,"area":null},{"id":"2411.13264","title":"Transformers with Sparse Attention for Granger Causality","created":"2024-11-20","cited_by_count":0,"area":null},{"id":"2411.17774","title":"Leaning Time-Varying Instruments for Identifying Causal Effects in Time-Series Data","created":"2024-11-26","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":"2505.09113","title":"Sequential Treatment Effect Estimation with Unmeasured Confounders","created":"2025-05-14","cited_by_count":0,"area":null},{"id":"2507.10809","title":"Uncovering Causal Relation Shifts in Event Sequences under Out-of-Domain Interventions","created":"2025-07-14","cited_by_count":0,"area":null},{"id":"2508.21722","title":"Inferring Effects of Major Events through Discontinuity Forecasting of Population Anxiety","created":"2025-08-29","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":"2510.15479","title":"Adversary-Free Counterfactual Prediction via Information-Regularized Representations","created":"2025-10-17","cited_by_count":0,"area":null},{"id":"2511.04361","title":"Causal Regime Detection in Energy Markets With Augmented Time Series Structural Causal Models","created":"2025-11-06","cited_by_count":0,"area":null},{"id":"2511.16006","title":"Synergizing Deconfounding and Temporal Generalization For Time-series Counterfactual Outcome Estimation","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":"2603.07431","title":"OrthoFormer: Instrumental Variable Estimation in Transformer Hidden States via Neural Control Functions","created":"2026-03-08","cited_by_count":0,"area":null},{"id":"2604.02472","title":"VALOR: Value-Aware Revenue Uplift Modeling with Treatment-Gated Representation for B2B Sales","created":"2026-04-02","cited_by_count":0,"area":null}],"next_cursor":"100"}