1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.LG2026
AROMMA: Unifying Olfactory Embeddings for Single Molecules and Mixtures
Dayoung Kang, JongWon Kim, Jiho Park +3
Public olfaction datasets are small and fragmented across single molecules and mixtures, limiting learning of generalizable odor representations. Recent works either learn single-m…
stat.ML2024★ 1 cited
Multifidelity linear regression for scientific machine learning from scarce data
Elizabeth Qian, Dayoung Kang, Vignesh Sella +1
Machine learning (ML) methods, which fit to data the parameters of a given parameterized model class, have garnered significant interest as potential methods for learning surrogate…