1 citations · 2 across the 4 of their papers we have counts for
4 papers
A Distributional Framework for Generative Modeling of Molecular Crystals
Michael Kilgour, Alex Dong, Mark E. Tuckerman +1
Molecular crystals are a highly polymorphic class of materials, with a single molecule commonly crystallizing via multiple packing patterns, making structure and property predictio…
MXtalTools: A Toolkit for Machine Learning on Molecular Crystals
Michael Kilgour, Mark E. Tuckerman, Jutta Rogal
We present MXtalTools, a flexible Python package for the data-driven modelling of molecular crystals, facilitating machine learning studies of the molecular solid state. MXtalTools…
Multi-Type Point Cloud Autoencoder: A Complete Equivariant Embedding for Molecule Conformation and Pose
Michael Kilgour, Mark Tuckerman, Jutta Rogal
Representations are a foundational component of any modelling protocol, including on molecules and molecular solids. For tasks that depend on knowledge of both molecular conformati…
Machine learning classification of local environments in molecular crystals
Daisuke Kuroshima, Michael Kilgour, Mark E. Tuckerman +1
Identifying local structural motifs and packing patterns of molecular solids is a challenging task for both simulation and experiment. We demonstrate two novel approaches to charac…