Zobrazeno 1 - 10
of 13
pro vyhledávání: '"Michael J. Willatt"'
Autor:
Sergey N. Pozdnyakov, Michael J. Willatt, Albert P. Bartók, Christoph Ortner, Gábor Csányi, Michele Ceriotti
The “quasi-constant” smooth overlap of atomic position and atom-centered symmetry function fingerprint manifolds recently discovered by Parsaeifard and Goedecker [J. Chem. Phys. 156, 034302 (2022)] are closely related to the degenerate pairs of c
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bcfd4683bd671e32fd14b528c1989040
Autor:
Guillaume Fraux, Markus Stricker, Michael J. Willatt, Alexander Goscinski, Max Veit, Félix Musil, Michele Ceriotti, Till Junge
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:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7479cb20122e9e823c5b124b818e699f
https://refubium.fu-berlin.de/handle/fub188/34517
https://refubium.fu-berlin.de/handle/fub188/34517
Autor:
Sergey Pozdnyakov, Christoph Ortner, Albert P. Bartók, Michael J. Willatt, Michele Ceriotti, Gábor Csányi
Publikováno v:
Physical Review Letters. 125
Many-body descriptors are widely used to represent atomic environments in the construction of machine learned interatomic potentials and more broadly for fitting, classification and embedding tasks on atomic structures. It was generally believed that
Publikováno v:
Handbook of Materials Modeling ISBN: 9783319429137
We briefly summarize the kernel regression approach, as used recently in materials modelling, to fitting functions, particularly potential energy surfaces, and highlight how the linear algebra framework can be used to both predict and train from line
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e274f55786000e601036b594e87bc8c0
https://doi.org/10.1007/978-3-319-44677-6_68
https://doi.org/10.1007/978-3-319-44677-6_68
Publikováno v:
Machine Learning in Chemistry: Data-Driven Algorithms, Learning Systems, and Predictions
ACS Symposium Series ISBN: 9780841235052
ACS Symposium Series
ACS Symposium Series-Machine Learning in Chemistry: Data-Driven Algorithms, Learning Systems, and Predictions
ACS Symposium Series ISBN: 9780841235052
ACS Symposium Series
ACS Symposium Series-Machine Learning in Chemistry: Data-Driven Algorithms, Learning Systems, and Predictions
This chapter discusses the importance of incorporating three-dimensional symmetries in the context of statistical learning models geared towards the interpolation of the tensorial properties of atomic-scale structures. We focus on Gaussian process re
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e3daf57667cbf371ce9c9953a6ee3c35
http://arxiv.org/abs/1904.01623
http://arxiv.org/abs/1904.01623
Publikováno v:
Journal of Chemical Theory and Computation
We present a scheme to obtain an inexpensive and reliable estimate of the uncertainty associated with the predictions of a machine-learning model of atomic and molecular properties. The scheme is based on resampling, with multiple models being genera
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fc6230b09c1ee9434d5a8a8b3481c87a
http://arxiv.org/abs/1809.07653
http://arxiv.org/abs/1809.07653
Publikováno v:
The Journal of chemical physics. 148(10)
Matsubara dynamics is the quantum-Boltzmann-conserving classical dynamics which remains when real-time coherences are taken out of the exact quantum Liouvillian [T. J. H. Hele et al., J. Chem. Phys. 142, 134103 (2015)]; because of a phase-term, it ca
Publikováno v:
Physical Chemistry Chemical Physics
Machine-learning of atomic-scale properties amounts to extracting correlations between structure, composition and the quantity that one wants to predict. Representing the input structure in a way that best reflects such correlations makes it possible
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::27dbad075519197445a018c2704f5109
Publikováno v:
The Journal of chemical physics. 142(19)
We recently obtained a quantum-Boltzmann-conserving classical dynamics by making a single change to the derivation of the “Classical Wigner” approximation. Here, we show that the further approximation of this “Matsubara dynamics” gives rise t