1 citations · 1 across the 1 of their papers we have counts for
2 papers
cond-mat.mtrl-sci2022★ 1 cited
By how much can closed-loop frameworks accelerate computational materials discovery?
Lance Kavalsky, Vinay I. Hegde, Eric Muckley +3
The implementation of automation and machine learning surrogatization within closed-loop computational workflows is an increasingly popular approach to accelerate materials discove…
stat.ML2018
Simple, Distributed, and Accelerated Probabilistic Programming
Dustin Tran, Matthew Hoffman, Dave Moore +5
We describe a simple, low-level approach for embedding probabilistic programming in a deep learning ecosystem. In particular, we distill probabilistic programming down to a single…