Showing cs.LGShow all
3 papers · 1 filter
cs.LG2025
Operator Learning at Machine Precision
Aras Bacho, Aleksei G. Sorokin, Xianjin Yang +6
Neural operator learning methods have garnered significant attention in scientific computing for their ability to approximate infinite-dimensional operators. However, increasing th…
cs.LG2025
Pruning Deep Neural Networks via a Combination of the Marchenko-Pastur Distribution and Regularization
Leonid Berlyand, Theo Bourdais, Houman Owhadi +1
Deep neural networks (DNNs) have brought significant advancements in various applications in recent years, such as image recognition, speech recognition, and natural language proce…
cs.LG2024
Minimal Variance Model Aggregation: A principled, non-intrusive, and versatile integration of black box models
Théo Bourdais, Houman Owhadi
Whether deterministic or stochastic, models can be viewed as functions designed to approximate a specific quantity of interest. We introduce Minimal Empirical Variance Aggregation…