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05/23/2023
Evaluation of the MACE Force Field Architecture: from Medicinal Chemistry to Materials Science
The MACE architecture represents the state of the art in the field of ma...
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10/09/2022
Hyperactive Learning (HAL) for Data-Driven Interatomic Potentials
Data-driven interatomic potentials have emerged as a powerful class of s...
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10/02/2022
Tensor-reduced atomic density representations
Density based representations of atomic environments that are invariant ...
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06/15/2022
MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields
Creating fast and accurate force fields is a long-standing challenge in ...
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05/31/2022
Nested sampling for physical scientists
We review Skilling's nested sampling (NS) algorithm for Bayesian inferen...
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05/13/2022
The Design Space of E(3)-Equivariant Atom-Centered Interatomic Potentials
The rapid progress of machine learning interatomic potentials over the p...
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04/30/2021
Ranking the information content of distance measures
Real-world data typically contain a large number of features that are of...
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11/25/2020
Symmetry-Aware Actor-Critic for 3D Molecular Design
Automating molecular design using deep reinforcement learning (RL) has t...
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09/09/2020
An Experimentally Driven Automated Machine Learned lnter-Atomic Potential for a Refractory Oxide
Understanding the structure and properties of refractory oxides are crit...
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06/21/2020
Learning the electronic density of states in condensed matter
The electronic density of states (DOS) quantifies the distribution of th...
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11/08/2019
Approximation of Potential Energy Surfaces with Spherical Harmonics
In this note we detail a framework to systematically derive polynomial b...
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10/22/2019
