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SchNetPack 2.0: A neural network toolbox for atomistic machine learning

SchNetPack 2.0: A neural network toolbox for atomistic machine learning

11 December 2022
Kristof T. Schütt
Stefaan S. P. Hessmann
Niklas W. A. Gebauer
Jonas Lederer
M. Gastegger
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Papers citing "SchNetPack 2.0: A neural network toolbox for atomistic machine learning"

36 / 36 papers shown
Title
MACE: Higher Order Equivariant Message Passing Neural Networks for Fast
  and Accurate Force Fields
MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields
Ilyes Batatia
D. P. Kovács
G. Simm
Christoph Ortner
Gábor Csányi
75
478
0
15 Jun 2022
Accurate Machine Learned Quantum-Mechanical Force Fields for
  Biomolecular Simulations
Accurate Machine Learned Quantum-Mechanical Force Fields for Biomolecular Simulations
Oliver T. Unke
M. Stohr
Stefan Ganscha
Thomas Unterthiner
Hartmut Maennel
...
Daniel Ahlin
M. Gastegger
L. M. Sandonas
A. Tkatchenko
Klaus-Robert Muller
AI4CE
65
18
0
17 May 2022
Learning Local Equivariant Representations for Large-Scale Atomistic
  Dynamics
Learning Local Equivariant Representations for Large-Scale Atomistic Dynamics
Albert Musaelian
Simon L. Batzner
A. Johansson
Lixin Sun
Cameron J. Owen
M. Kornbluth
Boris Kozinsky
89
452
0
11 Apr 2022
Automatic Identification of Chemical Moieties
Automatic Identification of Chemical Moieties
Jonas Lederer
M. Gastegger
Kristof T. Schütt
Michael C. Kampffmeyer
Klaus-Robert Muller
Oliver T. Unke
45
5
0
30 Mar 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
225
173
0
10 Sep 2021
SE(3)-equivariant prediction of molecular wavefunctions and electronic
  densities
SE(3)-equivariant prediction of molecular wavefunctions and electronic densities
Oliver T. Unke
Mihail Bogojeski
M. Gastegger
Mario Geiger
Tess E. Smidt
Klaus-Robert Muller
56
93
0
04 Jun 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
191
254
0
01 May 2021
Equivariant message passing for the prediction of tensorial properties
  and molecular spectra
Equivariant message passing for the prediction of tensorial properties and molecular spectra
Kristof T. Schütt
Oliver T. Unke
M. Gastegger
101
531
0
05 Feb 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
297
1,295
0
08 Jan 2021
TorchMD: A deep learning framework for molecular simulations
TorchMD: A deep learning framework for molecular simulations
Stefan Doerr
Maciej Majewski
Adria Pérez
Andreas Krämer
C. Clementi
Frank Noe
T. Giorgino
Gianni De Fabritiis
AI4CE
107
173
0
22 Dec 2020
Symmetry-Aware Actor-Critic for 3D Molecular Design
Symmetry-Aware Actor-Critic for 3D Molecular Design
G. Simm
Robert Pinsler
Gábor Csányi
José Miguel Hernández-Lobato
AI4CE
66
65
0
25 Nov 2020
Machine learning of solvent effects on molecular spectra and reactions
Machine learning of solvent effects on molecular spectra and reactions
M. Gastegger
Kristof T. Schütt
Klaus-Robert Muller
AI4CE
45
61
0
28 Oct 2020
Machine Learning Force Fields
Machine Learning Force Fields
Oliver T. Unke
Stefan Chmiela
H. E. Sauceda
M. Gastegger
I. Poltavsky
Kristof T. Schütt
A. Tkatchenko
K. Müller
AI4CE
101
913
0
14 Oct 2020
Kohn-Sham equations as regularizer: building prior knowledge into
  machine-learned physics
Kohn-Sham equations as regularizer: building prior knowledge into machine-learned physics
Li Li
Stephan Hoyer
Ryan Pederson
Ruoxi Sun
E. D. Cubuk
Patrick F. Riley
K. Burke
AI4CE
58
122
0
17 Sep 2020
Machine learning and excited-state molecular dynamics
Machine learning and excited-state molecular dynamics
Julia Westermayr
P. Marquetand
AI4CE
43
56
0
28 May 2020
Predicting molecular dipole moments by combining atomic partial charges
  and atomic dipoles
Predicting molecular dipole moments by combining atomic partial charges and atomic dipoles
M. Veit
D. Wilkins
Yang Yang
R. DiStasio
Michele Ceriotti
40
91
0
27 Mar 2020
Directional Message Passing for Molecular Graphs
Directional Message Passing for Molecular Graphs
Johannes Klicpera
Janek Groß
Stephan Günnemann
122
871
0
06 Mar 2020
Autonomous robotic nanofabrication with reinforcement learning
Autonomous robotic nanofabrication with reinforcement learning
Philipp Leinen
Malte Esders
Kristof T. Schütt
C. Wagner
K. Müller
F. Tautz
39
53
0
27 Feb 2020
Machine learning for molecular simulation
Machine learning for molecular simulation
Frank Noé
A. Tkatchenko
K. Müller
C. Clementi
AI4CE
73
663
0
07 Nov 2019
Equivariant Flows: sampling configurations for multi-body systems with
  symmetric energies
Equivariant Flows: sampling configurations for multi-body systems with symmetric energies
Jonas Köhler
Leon Klein
Frank Noé
73
91
0
02 Oct 2019
Deep neural network solution of the electronic Schrödinger equation
Deep neural network solution of the electronic Schrödinger equation
J. Hermann
Zeno Schätzle
Frank Noé
202
456
0
16 Sep 2019
Ab-Initio Solution of the Many-Electron Schrödinger Equation with Deep
  Neural Networks
Ab-Initio Solution of the Many-Electron Schrödinger Equation with Deep Neural Networks
David Pfau
J. Spencer
A. G. Matthews
W. Foulkes
72
462
0
05 Sep 2019
Unifying machine learning and quantum chemistry -- a deep neural network
  for molecular wavefunctions
Unifying machine learning and quantum chemistry -- a deep neural network for molecular wavefunctions
Kristof T. Schütt
M. Gastegger
A. Tkatchenko
K. Müller
R. Maurer
AI4CE
75
389
0
24 Jun 2019
Symmetry-adapted generation of 3d point sets for the targeted discovery
  of molecules
Symmetry-adapted generation of 3d point sets for the targeted discovery of molecules
Niklas W. A. Gebauer
M. Gastegger
Kristof T. Schütt
118
208
0
02 Jun 2019
Band gap prediction for large organic crystal structures with machine
  learning
Band gap prediction for large organic crystal structures with machine learning
B. Olsthoorn
R. Geilhufe
S. Borysov
A. Balatsky
AI4CE
34
75
0
30 Oct 2018
3D Steerable CNNs: Learning Rotationally Equivariant Features in
  Volumetric Data
3D Steerable CNNs: Learning Rotationally Equivariant Features in Volumetric Data
Maurice Weiler
Mario Geiger
Max Welling
Wouter Boomsma
Taco S. Cohen
3DPC
97
504
0
06 Jul 2018
Constrained Graph Variational Autoencoders for Molecule Design
Constrained Graph Variational Autoencoders for Molecule Design
Qi Liu
Miltiadis Allamanis
Marc Brockschmidt
Alexander L. Gaunt
BDL
73
455
0
23 May 2018
Tensor field networks: Rotation- and translation-equivariant neural
  networks for 3D point clouds
Tensor field networks: Rotation- and translation-equivariant neural networks for 3D point clouds
Nathaniel Thomas
Tess E. Smidt
S. Kearnes
Lusann Yang
Li Li
Kai Kohlhoff
Patrick F. Riley
3DPC
83
970
0
22 Feb 2018
VAMPnets: Deep learning of molecular kinetics
VAMPnets: Deep learning of molecular kinetics
Andreas Mardt
Luca Pasquali
Hao Wu
Frank Noé
60
545
0
16 Oct 2017
SchNet: A continuous-filter convolutional neural network for modeling
  quantum interactions
SchNet: A continuous-filter convolutional neural network for modeling quantum interactions
Kristof T. Schütt
Pieter-Jan Kindermans
Huziel Enoc Sauceda Felix
Stefan Chmiela
A. Tkatchenko
K. Müller
155
1,074
0
26 Jun 2017
Machine Learning Molecular Dynamics for the Simulation of Infrared
  Spectra
Machine Learning Molecular Dynamics for the Simulation of Infrared Spectra
M. Gastegger
J. Behler
P. Marquetand
AI4CE
31
334
0
16 May 2017
Neural Message Passing for Quantum Chemistry
Neural Message Passing for Quantum Chemistry
Justin Gilmer
S. Schoenholz
Patrick F. Riley
Oriol Vinyals
George E. Dahl
588
7,443
0
04 Apr 2017
By-passing the Kohn-Sham equations with machine learning
By-passing the Kohn-Sham equations with machine learning
Felix Brockherde
Leslie Vogt
Li Li
M. Tuckerman
K. Burke
K. Müller
AI4CE
64
606
0
09 Sep 2016
Gaussian Error Linear Units (GELUs)
Gaussian Error Linear Units (GELUs)
Dan Hendrycks
Kevin Gimpel
169
5,001
0
27 Jun 2016
TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed
  Systems
TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems
Martín Abadi
Ashish Agarwal
P. Barham
E. Brevdo
Zhiwen Chen
...
Pete Warden
Martin Wattenberg
Martin Wicke
Yuan Yu
Xiaoqiang Zheng
269
11,152
0
14 Mar 2016
Fast and Accurate Modeling of Molecular Atomization Energies with
  Machine Learning
Fast and Accurate Modeling of Molecular Atomization Energies with Machine Learning
M. Rupp
A. Tkatchenko
K. Müller
O. A. von Lilienfeld
AI4CE
179
1,590
0
12 Sep 2011
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