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Accurate Machine Learned Quantum-Mechanical Force Fields for
  Biomolecular Simulations

Accurate Machine Learned Quantum-Mechanical Force Fields for Biomolecular Simulations

17 May 2022
Oliver T. Unke
M. Stohr
Stefan Ganscha
Thomas Unterthiner
Hartmut Maennel
S. Kashubin
Daniel Ahlin
M. Gastegger
L. M. Sandonas
A. Tkatchenko
Klaus-Robert Muller
    AI4CE
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Papers citing "Accurate Machine Learned Quantum-Mechanical Force Fields for Biomolecular Simulations"

5 / 5 papers shown
Title
Scaling the leading accuracy of deep equivariant models to biomolecular
  simulations of realistic size
Scaling the leading accuracy of deep equivariant models to biomolecular simulations of realistic size
Albert Musaelian
A. Johansson
Simon L. Batzner
Boris Kozinsky
14
48
0
20 Apr 2023
Structure-based drug design with geometric deep learning
Structure-based drug design with geometric deep learning
Clemens Isert
Kenneth Atz
G. Schneider
27
104
0
19 Oct 2022
Inverse design of 3d molecular structures with conditional generative
  neural networks
Inverse design of 3d molecular structures with conditional generative neural networks
Niklas W. A. Gebauer
M. Gastegger
Stefaan S. P. Hessmann
Klaus-Robert Muller
Kristof T. Schütt
AI4CE
173
125
0
10 Sep 2021
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
242
0
01 May 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
138
444
0
16 Sep 2019
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