Claire Boyer

A primer on linear classification with missing data

2024 · arXiv (Cornell University)

Supervised learning with missing data aims at building the best prediction of a target output based on partially-observed inputs. Major approaches to address this problem can be decomposed into $(i)$ impute-then-predict strategies, which first fill …

Physics-informed kernel learning

2024 · arXiv (Cornell University)

Physics-informed machine learning typically integrates physical priors into the learning process by minimizing a loss function that includes both a data-driven term and a partial differential equation (PDE) regularization. Building on the formulation of the …

Taking a Big Step: Large Learning Rates in Denoising Score Matching Prevent Memorization

2025 · arXiv (Cornell University)

Denoising score matching plays a pivotal role in the performance of diffusion-based generative models. However, the empirical optimal score--the exact solution to the denoising score matching--leads to memorization, where generated samples replicate the training data. …