322 citations · 432 across the 23 of their papers we have counts for
3 papers · 2 filters
A U-turn on Double Descent: Rethinking Parameter Counting in Statistical Learning
Alicia Curth, Alan Jeffares, Mihaela van der Schaar
Conventional statistical wisdom established a well-understood relationship between model complexity and prediction error, typically presented as a U-shaped curve reflecting a trans…
Accounting For Informative Sampling When Learning to Forecast Treatment Outcomes Over Time
Toon Vanderschueren, Alicia Curth, Wouter Verbeke +1
Machine learning (ML) holds great potential for accurately forecasting treatment outcomes over time, which could ultimately enable the adoption of more individualized treatment str…
In Search of Insights, Not Magic Bullets: Towards Demystification of the Model Selection Dilemma in Heterogeneous Treatment Effect Estimation
Alicia Curth, Mihaela van der Schaar
Personalized treatment effect estimates are often of interest in high-stakes applications -- thus, before deploying a model estimating such effects in practice, one needs to be sur…