Alicia Curth
16 papers · 2021–2024 · 5 conferences · across top CS/AI conferences
Achievements
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π Conference Polyglot (5) π Cross-Pollinator (13) π Interdisciplinary Bridge π§ Keyword Pioneer π Renaissance Researcher (6)
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Renaissance Researcher
(6)
π€
Dynamic Duo
(15)
π
Triple Crown
π
Keyword Champion
(3)
β‘
Prolific Year
(5)
ποΈ
Keyword Collector
(54)
π
Century Club
(16)
Conferences
NIPS (6)
ICML (4)
ICLR (3)
AISTATS (2)
CLEAR (1)
Top co-authors
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