2.1k citations · 6k across the 29 of their papers we have counts for
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The AFLOW Fleet for Materials Discovery
Cormac Toher, Corey Oses, David Hicks +48
The traditional paradigm for materials discovery has been recently expanded to incorporate substantial data driven research. With the intent to accelerate the development and the d…
AFLOW-ML: A RESTful API for machine-learning predictions of materials properties
Eric Gossett, Cormac Toher, Corey Oses +8
Machine learning approaches, enabled by the emergence of comprehensive databases of materials properties, are becoming a fruitful direction for materials analysis. As a result, a p…
Deep Reinforcement Learning for De-Novo Drug Design
Mariya Popova, Olexandr Isayev, Alexander Tropsha
We propose a novel computational strategy for de novo design of molecules with desired properties termed ReLeaSE (Reinforcement Learning for Structural Evolution). Based on deep an…
ANI-1: A data set of 20M off-equilibrium DFT calculations for organic molecules
Justin S. Smith, Olexandr Isayev, Adrian E. Roitberg
One of the grand challenges in modern theoretical chemistry is designing and implementing approximations that expedite ab initio methods without loss of accuracy. Machine learning…