10 citations · 30 across the 9 of their papers we have counts for
4 papers · 1 filter
QT-Net: Rethinking Evaluation of AI Models in Atomic Chemical Space
Pablo Martínez Crespo, Stefano Ribes, Martin Rahm +6
Atomic properties such as partial charges or multipoles encode chemically meaningful information that can inform downstream molecular property prediction, but their evaluation as m…
OXtal: An All-Atom Diffusion Model for Organic Crystal Structure Prediction
Emily Jin, Andrei Cristian Nica, Mikhail Galkin +8
Accurately predicting experimentally realizable 3D molecular crystal structures from their 2D chemical graphs is a long-standing open challenge in computational chemistry called cr…
Using Multiple Vector Channels Improves E(n)-Equivariant Graph Neural Networks
Daniel Levy, Sékou-Oumar Kaba, Carmelo Gonzales +2
We present a natural extension to E(n)-equivariant graph neural networks that uses multiple equivariant vectors per node. We formulate the extension and show that it improves perfo…
The Open MatSci ML Toolkit: A Flexible Framework for Machine Learning in Materials Science
Santiago Miret, Kin Long Kelvin Lee, Carmelo Gonzales +2
We present the Open MatSci ML Toolkit: a flexible, self-contained, and scalable Python-based framework to apply deep learning models and methods on scientific data with a specific…