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High Accuracy Uncertainty-Aware Interatomic Force Modeling with
  Equivariant Bayesian Neural Networks

High Accuracy Uncertainty-Aware Interatomic Force Modeling with Equivariant Bayesian Neural Networks

5 April 2023
Tim Rensmeyer
Benjamin Craig
D. Kramer
Oliver Niggemann
    BDL
ArXivPDFHTML

Papers citing "High Accuracy Uncertainty-Aware Interatomic Force Modeling with Equivariant Bayesian Neural Networks"

3 / 3 papers shown
Title
SpookyNet: Learning Force Fields with Electronic Degrees of Freedom and
  Nonlocal Effects
SpookyNet: Learning Force Fields with Electronic Degrees of Freedom and Nonlocal Effects
Oliver T. Unke
Stefan Chmiela
M. Gastegger
Kristof T. Schütt
H. E. Sauceda
K. Müller
142
244
0
01 May 2021
E(3)-Equivariant Graph Neural Networks for Data-Efficient and Accurate
  Interatomic Potentials
E(3)-Equivariant Graph Neural Networks for Data-Efficient and Accurate Interatomic Potentials
Simon L. Batzner
Albert Musaelian
Lixin Sun
Mario Geiger
J. Mailoa
M. Kornbluth
N. Molinari
Tess E. Smidt
Boris Kozinsky
190
1,229
0
08 Jan 2021
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
247
9,109
0
06 Jun 2015
1