Personne
Guillaume André Jean Fraux
Publications associées (8)
Surface segregation in high-entropy alloys from alchemical machine learning
Michele Ceriotti, Guillaume André Jean Fraux, Arslan Mazitov, Sandip De, Nataliya Lopanitsyna
High-entropy alloys (HEAs), containing several metallic elements in near-equimolar proportions, have long been of interest for their unique mechanical properties. More recently, they have emerged as a promising platform for the development of novel heterog ...
Bristol2024Modeling high-entropy transition metal alloys with alchemical compression
Michele Ceriotti, Guillaume André Jean Fraux, Sandip De, Nataliya Lopanitsyna
Alloys composed of several elements in roughly equimolar composition, often referred to as high-entropy alloys, have long been of interest for their thermodynamics and peculiar mechanical properties, and more recently for their potential application in cat ...
AMER PHYSICAL SOC2023Unified theory of atom-centered representations and message-passing machine-learning schemes
Michele Ceriotti, Guillaume André Jean Fraux, Sergey Pozdnyakov, Jigyasa Nigam
Data-driven schemes that associate molecular and crystal structures with their microscopic properties share the need for a concise, effective description of the arrangement of their atomic constituents. Many types of models rely on descriptions of atom-cen ...
AIP Publishing2022Efficient implementation of atom-density representations
Michele Ceriotti, Till Junge, Guillaume André Jean Fraux, Félix Benedito Clément Musil, Michael John Willatt, Max David Veit, Alexander Jan Goscinski
Physically motivated and mathematically robust atom-centered representations of molecular structures are key to the success of modern atomistic machine learning. They lie at the foundation of a wide range of methods to predict the properties of both materi ...
2021Chemiscope: interactive structure-property explorer for materials and molecules
Michele Ceriotti, Guillaume André Jean Fraux
The number of materials or molecules that can be created by combining different chemical elements in various proportions and spatial arrangements is enormous. Computational chemistry can be used to generate databases containing billions of potential struct ...
2020Structure-property maps with Kernel principal covariates regression
Michele Ceriotti, Guillaume André Jean Fraux, Benjamin Aaron Helfrecht
Data analyses based on linear methods constitute the simplest, most robust, and transparent approaches to the automatic processing of large amounts of data for building supervised or unsupervised machine learning models. Principal covariates regression (PC ...
2020DUBS: A Framework for Developing Directory of Useful Benchmarking Sets for Virtual Screening
Benchmarking is a crucial step in evaluating virtual screening methods for drug discovery. One major issue that arises among benchmarking data sets is a lack of a standardized format for representing the protein and ligand structures used to benchmark the ...
2020Fermi resonance in CO2: Mode assignment and quantum nuclear effects from first principles molecular dynamics
Sara Bonella, Guillaume André Jean Fraux
Vibrational spectroscopy is a fundamental tool to investigate local atomic arrangements and the effect of the environment, provided that the spectral features can be correctly assigned. This can be challenging in experiments and simulations when double pea ...
Amer Inst Physics2017