Stefan Feuerriegel
36 papers · 2018–2025 · 12 conferences · across top CS/AI conferences
Achievements
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(10)
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(109)
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Century Club
(36)
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(8)
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Trend Setter
Conferences
ICLR (10)
ICML (6)
NIPS (5)
EMNLP (4)
AAAI (3)
ACL (2)
AISTATS (1)
CLEAR (1)
COLING (1)
MLHC (1)
NAACL (1)
UAI (1)
Top co-authors
Keywords
causal inference
(8)
question answering
(6)
personalized medicine
(3)
treatment effect
(3)
off-policy learning
(3)
domain adaptation
(3)
time-varying confounder
(2)
contrastive learning
(2)
partial identification
(2)
heterogeneous treatment effect
(2)
normalizing flow
(2)
weak supervision
(2)
sensitivity analysis
(2)
potential outcome
(2)
density estimation
(1)
text classification
(1)
zero-shot learning
(1)
natural language processing
(1)
reinforcement learning
(1)
active learning
(1)
Papers
Stabilized Neural Prediction of Potential Outcomes in Continuous Time
ICLR 2025
Learning Representations of Instruments for Partial Identification of Treatment Effects
ICML 2025
Constructing Confidence Intervals for Average Treatment Effects from Multiple Datasets
ICLR 2025
Differentially private learners for heterogeneous treatment effects
ICLR 2025
Model-agnostic meta-learners for estimating heterogeneous treatment effects over time
ICLR 2025
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
NIPS 2024
Fair Off-Policy Learning from Observational Data
ICML 2024
HQP: A Human-Annotated Dataset for Detecting Online Propaganda
ACL 2024
Quantifying Aleatoric Uncertainty of the Treatment Effect: A Novel Orthogonal Learner
NIPS 2024
A Neural Framework for Generalized Causal Sensitivity Analysis
ICLR 2024
Sequential Deconfounding for Causal Inference with Unobserved Confounders
CLEAR 2024
Meta-Learners for Partially-Identified Treatment Effects Across Multiple Environments
ICML 2024
Bayesian Neural Controlled Differential Equations for Treatment Effect Estimation
ICLR 2024
Partial Counterfactual Identification of Continuous Outcomes with a Curvature Sensitivity Model
NIPS 2023
Sharp Bounds for Generalized Causal Sensitivity Analysis
NIPS 2023
Reliable Off-Policy Learning for Dosage Combinations
NIPS 2023
Estimating Average Causal Effects from Patient Trajectories
AAAI 2023
Estimating Conditional Average Treatment Effects with Missing Treatment Information
AISTATS 2023
Contrastive Learning for Unsupervised Domain Adaptation of Time Series
ICLR 2023
Estimating individual treatment effects under unobserved confounding using binary instruments
ICLR 2023
Normalizing Flows for Interventional Density Estimation
ICML 2023
QA Domain Adaptation using Hidden Space Augmentation and Self-Supervised Contrastive Adaptation
EMNLP 2022
Causal Transformer for Estimating Counterfactual Outcomes
ICML 2022
Interpretable Off-Policy Learning via Hyperbox Search
ICML 2022
Generalizing off-policy learning under sample selection bias
UAI 2022
Learning Optimal Dynamic Treatment Regimes Using Causal Tree Methods in Medicine
MLHC 2022
DocParser: Hierarchical Document Structure Parsing from Renderings
AAAI 2021
Contrastive Domain Adaptation for Question Answering using Limited Text Corpora
EMNLP 2021
Sample Complexity Bounds for RNNs with Application to Combinatorial Graph Problems (Student Abstract)
AAAI 2020
Learning a Cost-Effective Annotation Policy for Question Answering
EMNLP 2020
IntKB: A Verifiable Interactive Framework for Knowledge Base Completion
COLING 2020
RankQA: Neural Question Answering with Answer Re-Ranking
ACL 2019
Learning Interpretable Negation Rules via Weak Supervision at Document Level: A Reinforcement Learning Approach
NAACL 2019
Adaptive Document Retrieval for Deep Question Answering
EMNLP 2018