Stefan Feuerriegel

Consistent End-to-End Estimation for Counterfactual Fairness CLeaR 2026 Constructing Confidence Intervals for Average Treatment Effects from Multiple Datasets ICLR 2025 Differentially private learners for heterogeneous treatment effects ICLR 2025 Learning Representations of Instruments for Partial Identification of Treatment Effects ICML 2025 Model-agnostic meta-learners for estimating heterogeneous treatment effects over time ICLR 2025 Stabilized Neural Prediction of Potential Outcomes in Continuous Time ICLR 2025 A Neural Framework for Generalized Causal Sensitivity Analysis ICLR 2024 Bayesian Neural Controlled Differential Equations for Treatment Effect Estimation ICLR 2024 Bounds on Representation-Induced Confounding Bias for Treatment Effect Estimation ICLR 2024 Causal Fairness under Unobserved Confounding: A Neural Sensitivity Framework ICLR 2024 DiffPO: A causal diffusion model for learning distributions of potential outcomes NeurIPS 2024 Fair Off-Policy Learning from Observational Data ICML 2024 HQP: A Human-Annotated Dataset for Detecting Online Propaganda ACL 2024 Meta-Learners for Partially-Identified Treatment Effects Across Multiple Environments ICML 2024 Quantifying Aleatoric Uncertainty of the Treatment Effect: A Novel Orthogonal Learner NeurIPS 2024 Sequential Deconfounding for Causal Inference with Unobserved Confounders CLeaR 2024 Contrastive Learning for Unsupervised Domain Adaptation of Time Series ICLR 2023 Estimating Average Causal Effects from Patient Trajectories AAAI 2023 Estimating Conditional Average Treatment Effects with Missing Treatment Information AISTATS 2023 Estimating individual treatment effects under unobserved confounding using binary instruments ICLR 2023 Normalizing Flows for Interventional Density Estimation ICML 2023 Partial Counterfactual Identification of Continuous Outcomes with a Curvature Sensitivity Model NeurIPS 2023 Reliable Off-Policy Learning for Dosage Combinations NeurIPS 2023 Sharp Bounds for Generalized Causal Sensitivity Analysis NeurIPS 2023 Causal Transformer for Estimating Counterfactual Outcomes ICML 2022 Generalizing off-policy learning under sample selection bias UAI 2022 Interpretable Off-Policy Learning via Hyperbox Search ICML 2022 Learning Optimal Dynamic Treatment Regimes Using Causal Tree Methods in Medicine MLHC 2022 QA Domain Adaptation using Hidden Space Augmentation and Self-Supervised Contrastive Adaptation EMNLP 2022 Contrastive Domain Adaptation for Question Answering using Limited Text Corpora EMNLP 2021 DocParser: Hierarchical Document Structure Parsing from Renderings AAAI 2021 IntKB: A Verifiable Interactive Framework for Knowledge Base Completion COLING 2020 Learning a Cost-Effective Annotation Policy for Question Answering EMNLP 2020 Sample Complexity Bounds for RNNs with Application to Combinatorial Graph Problems (Student Abstract) AAAI 2020 Learning Interpretable Negation Rules via Weak Supervision at Document Level: A Reinforcement Learning Approach NAACL 2019 RankQA: Neural Question Answering with Answer Re-Ranking ACL 2019 Adaptive Document Retrieval for Deep Question Answering EMNLP 2018