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cs.LG2021★ 2 cited
Compressing Heavy-Tailed Weight Matrices for Non-Vacuous Generalization Bounds
John Y. Shin
Heavy-tailed distributions have been studied in statistics, random matrix theory, physics, and econometrics as models of correlated systems, among other domains. Further, heavy-tai…
cs.LG2021
An Energy-Based View of Graph Neural Networks
John Y. Shin, Prathamesh Dharangutte
Graph neural networks are a popular variant of neural networks that work with graph-structured data. In this work, we consider combining graph neural networks with the energy-based…