:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Frauen, Dennis, Brockschmidt, Marie, Hess, Konstantin, Ma, Haorui, Ma, Yuchen, Maarouf, Abdurahman, Schröder, Maresa, Schweisthal, Jonas, Wang, Yuxin, Deviyani, Athiya, Parbhoo, Sonali, Krishnan, Rahul G., Feuerriegel, Stefan
Format:	Preprint
Published:	2026
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2605.25998
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Conformal Prediction for Causal Effects of Continuous Treatments
by: Schröder, Maresa, et al.
Published: (2024)

Constructing Confidence Intervals for Average Treatment Effects from Multiple Datasets
by: Wang, Yuxin, et al.
Published: (2024)

Learning Representations of Instruments for Partial Identification of Treatment Effects
by: Schweisthal, Jonas, et al.
Published: (2024)

Amortizing Causal Sensitivity Analysis via Prior Data-Fitted Networks
by: Javurek, Emil, et al.
Published: (2026)

Assessing the robustness of heterogeneous treatment effects in survival analysis under informative censoring
by: Wang, Yuxin, et al.
Published: (2025)

Orthogonal Survival Learners for Estimating Heterogeneous Treatment Effects from Time-to-Event Data
by: Frauen, Dennis, et al.
Published: (2025)

SurvDiff: A Diffusion Model for Generating Synthetic Data in Survival Analysis
by: Brockschmidt, Marie, et al.
Published: (2025)

Adaptive Experimentation for Censored Survival Outcomes
by: Wang, Yuxin, et al.
Published: (2026)

Nonparametric LLM Evaluation from Preference Data
by: Frauen, Dennis, et al.
Published: (2026)

Causal Fairness under Unobserved Confounding: A Neural Sensitivity Framework
by: Schröder, Maresa, et al.
Published: (2023)

LLM-Driven Treatment Effect Estimation Under Inference Time Text Confounding
by: Ma, Yuchen, et al.
Published: (2025)

Orthogonal Representation Learning for Estimating Causal Quantities
by: Melnychuk, Valentyn, et al.
Published: (2025)

An Orthogonal Learner for Individualized Outcomes in Markov Decision Processes
by: Javurek, Emil, et al.
Published: (2025)

Contextual Metric Meta-Evaluation by Measuring Local Metric Accuracy
by: Deviyani, Athiya, et al.
Published: (2025)

Targeted Synthetic Control Method
by: Wang, Yuxin, et al.
Published: (2026)

DeepBlip: Estimating Conditional Average Treatment Effects Over Time
by: Ma, Haorui, et al.
Published: (2025)

Overlap-Adaptive Regularization for Conditional Average Treatment Effect Estimation
by: Melnychuk, Valentyn, et al.
Published: (2025)

ConfoundingSHAP: Quantifying confounding strength in causal inference
by: Brockschmidt, Marie, et al.
Published: (2026)

Model-agnostic meta-learners for estimating heterogeneous treatment effects over time
by: Frauen, Dennis, et al.
Published: (2024)

Predicting Startup Success Using Large Language Models: A Novel In-Context Learning Approach
by: Maarouf, Abdurahman, et al.
Published: (2026)

The Virality of Hate Speech on Social Media
by: Maarouf, Abdurahman, et al.
Published: (2022)

A Fused Large Language Model for Predicting Startup Success
by: Maarouf, Abdurahman, et al.
Published: (2024)

Analyzing User Characteristics of Hate Speech Spreaders on Social Media
by: Geissler, Dominique, et al.
Published: (2023)

Generative AI may backfire for counterspeech
by: Bär, Dominik, et al.
Published: (2024)

A Diffusion-Based Method for Learning the Multi-Outcome Distribution of Medical Treatments
by: Ma, Yuchen, et al.
Published: (2025)

DiffPO: A causal diffusion model for learning distributions of potential outcomes
by: Ma, Yuchen, et al.
Published: (2024)

Orthogonal Learner for Estimating Heterogeneous Long-Term Treatment Effects
by: Ma, Haorui, et al.
Published: (2026)

Meta-Learners for Partially-Identified Treatment Effects Across Multiple Environments
by: Schweisthal, Jonas, et al.
Published: (2024)

Foundation Models for Causal Inference via Prior-Data Fitted Networks
by: Ma, Yuchen, et al.
Published: (2025)

Causal machine learning for predicting treatment outcomes
by: Feuerriegel, Stefan, et al.
Published: (2024)

Efficient and Sharp Off-Policy Learning under Unobserved Confounding
by: Hess, Konstantin, et al.
Published: (2025)

Debiased neural operators for estimating functionals
by: Hess, Konstantin, et al.
Published: (2026)

Bayesian Neural Controlled Differential Equations for Treatment Effect Estimation
by: Hess, Konstantin, et al.
Published: (2023)

IGC-Net for conditional average potential outcome estimation over time
by: Hess, Konstantin, et al.
Published: (2024)

HQP: A Human-Annotated Dataset for Detecting Online Propaganda
by: Maarouf, Abdurahman, et al.
Published: (2023)

Beyond Means: A Dynamic Framework for Predicting Customer Satisfaction
by: Naumzik, Christof, et al.
Published: (2025)

Treatment Effect Estimation for Optimal Decision-Making
by: Frauen, Dennis, et al.
Published: (2025)

Generalized Bayes for Causal Inference
by: Javurek, Emil, et al.
Published: (2026)

Causal Inference on Networks under Misspecified Exposure Mappings: A Partial Identification Framework
by: Schröder, Maresa, et al.
Published: (2026)

Why LLMs Fail at Causal Discovery and How Interventional Agents Escape
by: Roy, Amartya, et al.
Published: (2026)