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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…
cs.LG2020
Graph Learning for Inverse Landscape Genetics
Prathamesh Dharangutte, Christopher Musco
The problem of inferring unknown graph edges from numerical data at a graph's nodes appears in many forms across machine learning. We study a version of this problem that arises in…