Zobrazeno 1 - 10
of 157
pro vyhledávání: '"A. Fraux"'
Autor:
Litman, Yair, Kapil, Venkat, Feldman, Yotam M. Y., Tisi, Davide, Begušić, Tomislav, Fidanyan, Karen, Fraux, Guillaume, Higer, Jacob, Kellner, Matthias, Li, Tao E., Pós, Eszter S., Stocco, Elia, Trenins, George, Hirshberg, Barak, Rossi, Mariana, Ceriotti, Michele
Atomic-scale simulations have progressed tremendously over the past decade, largely due to the availability of machine-learning interatomic potentials. These potentials combine the accuracy of electronic structure calculations with the ability to rea
Externí odkaz:
http://arxiv.org/abs/2405.15224
Autor:
Mazitov, Arslan, Springer, Maximilian A., Lopanitsyna, Nataliya, Fraux, Guillaume, De, Sandip, Ceriotti, Michele
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 h
Externí odkaz:
http://arxiv.org/abs/2310.07604
Spherical harmonics provide a smooth, orthogonal, and symmetry-adapted basis to expand functions on a sphere, and they are used routinely in physical and theoretical chemistry as well as in different fields of science and technology, from geology and
Externí odkaz:
http://arxiv.org/abs/2302.08381
Autor:
Lopanitsyna, Nataliya, Fraux, Guillaume, Springer, Maximilian A., De, Sandip, Ceriotti, Michele
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
Externí odkaz:
http://arxiv.org/abs/2212.13254
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 at
Externí odkaz:
http://arxiv.org/abs/2202.01566
Autor:
Mouton, Valentin, Rigaud, Emmanuel, Chevrel-Fraux, Cyril, Casanova, Pierre, Perret-Liaudet, Joël
Publikováno v:
In Finite Elements in Analysis & Design December 2024 242
Autor:
Musil, Félix, Veit, Max, Goscinski, Alexander, Fraux, Guillaume, Willatt, Michael J., Stricker, Markus, Junge, Till, Ceriotti, Michele
Physically-motivated and mathematically robust atom-centred representations of molecular structures are key to the success of modern atomistic machine learning (ML) methods. They lie at the foundation of a wide range of methods to predict the propert
Externí odkaz:
http://arxiv.org/abs/2101.08814
Eficient, physically-inspired descriptors of the structure and composition of molecules and materials play a key role in the application of machine-learning techniques to atomistic simulations. The proliferation of approaches, as well as the fact tha
Externí odkaz:
http://arxiv.org/abs/2009.02741
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 regressi
Externí odkaz:
http://arxiv.org/abs/2002.05076
Autor:
Philip Loche, Alexander Goscinski, Guillaume Fraux, Victor Paul Principe, Benjamin Aaron Helfrecht, Sergei Kliavinek, Michele Ceriotti, Rose Kathleen Cersonsky
Publikováno v:
Open Research Europe, Vol 3 (2023)
Easy-to-use libraries such as scikit-learn have accelerated the adoption and application of machine learning (ML) workflows and data-driven methods. While many of the algorithms implemented in these libraries originated in specific scientific fields,
Externí odkaz:
https://doaj.org/article/0fba537f22354630beea592541b90f61