Alicia Curth

16 papers · 2021–2024 · 5 conferences · across top CS/AI conferences

Achievements

🌍 Conference Polyglot (5) 🐝 Cross-Pollinator (13) 🗺️ Taxonomy Completionist (28) 🌉 Interdisciplinary Bridge 🧭 Keyword Pioneer 🌈 Renaissance Researcher (6) 🤝 Dynamic Duo (15) 👑 Triple Crown 🏆 Keyword Champion (3) ⚡ Prolific Year (5) 🗃️ Keyword Collector (54) 💎 Century Club (16)

Conferences

NIPS (6) ICML (4) ICLR (3) AISTATS (2) CLEAR (1)

Top co-authors

Mihaela van der Schaar (15) Alihan Hüyük (2) Alan Jeffares (2) Jonathan Crabbe (1) Ioana Bica (1) Zhaozhi Qian (1) Dennis Frauen (1) Alex Chan (1) Toon Vanderschueren (1) Javier Gonzalez (1)

Keywords

causal inference (8) heterogeneous treatment effect (6) covariate shift (3) potential outcome (3) treatment effect (2) survival analysis (2) treatment effect estimation (2) domain adaptation (1) model selection (1) double descent (1) nonparametric estimation (1) gradient boosting (1) generalization error (1) model complexity (1) inductive bia (1) neural network training (1) conditional distribution (1) hyperparameter tuning (1) feature importance (1) informative sampling (1)

Papers

A Neural Framework for Generalized Causal Sensitivity Analysis ICLR 2024

Deep Learning Through A Telescoping Lens: A Simple Model Provides Empirical Insights On Grokking, Gradient Boosting & Beyond NIPS 2024

Defining Expertise: Applications to Treatment Effect Estimation ICLR 2024

Cautionary Tales on Synthetic Controls in Survival Analyses CLEAR 2024

Accounting For Informative Sampling When Learning to Forecast Treatment Outcomes Over Time ICML 2023

A U-turn on Double Descent: Rethinking Parameter Counting in Statistical Learning NIPS 2023

Understanding the Impact of Competing Events on Heterogeneous Treatment Effect Estimation from Time-to-Event Data AISTATS 2023

Adaptive Identification of Populations with Treatment Benefit in Clinical Trials: Machine Learning Challenges and Solutions ICML 2023

In Search of Insights, Not Magic Bullets: Towards Demystification of the Model Selection Dilemma in Heterogeneous Treatment Effect Estimation ICML 2023

HyperImpute: Generalized Iterative Imputation with Automatic Model Selection ICML 2022

Inverse Online Learning: Understanding Non-Stationary and Reactionary Policies ICLR 2022

Benchmarking Heterogeneous Treatment Effect Models through the Lens of Interpretability NIPS 2022

On Inductive Biases for Heterogeneous Treatment Effect Estimation NIPS 2021

Nonparametric Estimation of Heterogeneous Treatment Effects: From Theory to Learning Algorithms AISTATS 2021

SurvITE: Learning Heterogeneous Treatment Effects from Time-to-Event Data NIPS 2021

Estimating Multi-cause Treatment Effects via Single-cause Perturbation NIPS 2021