55 citations · 55 across the 1 of their papers we have counts for
4 papers · 1 filter
Data Augmentation for Compositional Data: Advancing Predictive Models of the Microbiome
Elliott Gordon-Rodriguez, Thomas P. Quinn, John P. Cunningham
Data augmentation plays a key role in modern machine learning pipelines. While numerous augmentation strategies have been studied in the context of computer vision and natural lang…
On the Normalizing Constant of the Continuous Categorical Distribution
Elliott Gordon-Rodriguez, Gabriel Loaiza-Ganem, Andres Potapczynski +1
Probability distributions supported on the simplex enjoy a wide range of applications across statistics and machine learning. Recently, a novel family of such distributions has bee…
Uses and Abuses of the Cross-Entropy Loss: Case Studies in Modern Deep Learning
Elliott Gordon-Rodriguez, Gabriel Loaiza-Ganem, Geoff Pleiss +1
Modern deep learning is primarily an experimental science, in which empirical advances occasionally come at the expense of probabilistic rigor. Here we focus on one such example; n…
The continuous categorical: a novel simplex-valued exponential family
Elliott Gordon-Rodriguez, Gabriel Loaiza-Ganem, John P. Cunningham
Simplex-valued data appear throughout statistics and machine learning, for example in the context of transfer learning and compression of deep networks. Existing models for this cl…