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Detect the Interactions that Matter in Matter: Geometric Attention for
  Many-Body Systems

Detect the Interactions that Matter in Matter: Geometric Attention for Many-Body Systems

4 June 2021
Thorben Frank
Stefan Chmiela
ArXivPDFHTML

Papers citing "Detect the Interactions that Matter in Matter: Geometric Attention for Many-Body Systems"

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
174
246
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
206
1,240
0
08 Jan 2021
Deep neural network solution of the electronic Schrödinger equation
Deep neural network solution of the electronic Schrödinger equation
J. Hermann
Zeno Schätzle
Frank Noé
149
446
0
16 Sep 2019
1