55 citations · 109 across the 7 of their papers we have counts for
5 papers · 1 filter
Conformation Generation using Transformer Flows
Sohil Atul Shah, Vladlen Koltun
Estimating three-dimensional conformations of a molecular graph allows insight into the molecule's biological and chemical functions. Fast generation of valid conformations is thus…
Auto-decoding Graphs
Sohil Atul Shah, Vladlen Koltun
We present an approach to synthesizing new graph structures from empirically specified distributions. The generative model is an auto-decoder that learns to synthesize graphs from…
Understanding the (un)interpretability of natural image distributions using generative models
Ryen Krusinga, Sohil Shah, Matthias Zwicker +2
Probability density estimation is a classical and well studied problem, but standard density estimation methods have historically lacked the power to model complex and high-dimensi…
Deep Continuous Clustering
Sohil Atul Shah, Vladlen Koltun
Clustering high-dimensional datasets is hard because interpoint distances become less informative in high-dimensional spaces. We present a clustering algorithm that performs nonlin…
Stabilizing Adversarial Nets With Prediction Methods
Abhay Yadav, Sohil Shah, Zheng Xu +2
Adversarial neural networks solve many important problems in data science, but are notoriously difficult to train. These difficulties come from the fact that optimal weights for ad…