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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

8 January 2021
Simon L. Batzner
Albert Musaelian
Lixin Sun
Mario Geiger
J. Mailoa
M. Kornbluth
N. Molinari
Tess E. Smidt
Boris Kozinsky
ArXivPDFHTML

Papers citing "E(3)-Equivariant Graph Neural Networks for Data-Efficient and Accurate Interatomic Potentials"

50 / 396 papers shown
Title
Neural Approximate Mirror Maps for Constrained Diffusion Models
Neural Approximate Mirror Maps for Constrained Diffusion Models
Berthy Feng
Ricardo Baptista
Katherine Bouman
MedIm
DiffM
48
3
0
18 Jun 2024
Learning Color Equivariant Representations
Learning Color Equivariant Representations
Felix O'Mahony
Yulong Yang
Christine Allen-Blanchette
28
0
0
13 Jun 2024
Equivariance via Minimal Frame Averaging for More Symmetries and
  Efficiency
Equivariance via Minimal Frame Averaging for More Symmetries and Efficiency
Yuchao Lin
Jacob Helwig
Shurui Gui
Shuiwang Ji
42
7
0
11 Jun 2024
Equivariant Neural Tangent Kernels
Equivariant Neural Tangent Kernels
Philipp Misof
Pan Kessel
Jan E. Gerken
64
0
0
10 Jun 2024
Grounding Continuous Representations in Geometry: Equivariant Neural Fields
Grounding Continuous Representations in Geometry: Equivariant Neural Fields
David R. Wessels
David M. Knigge
Samuele Papa
Riccardo Valperga
Sharvaree P. Vadgama
E. Gavves
Erik J. Bekkers
52
7
0
09 Jun 2024
Infusing Self-Consistency into Density Functional Theory Hamiltonian
  Prediction via Deep Equilibrium Models
Infusing Self-Consistency into Density Functional Theory Hamiltonian Prediction via Deep Equilibrium Models
Zun Wang
Chang-Shu Liu
Nianlong Zou
He Zhang
Xinran Wei
Lin Huang
Lijun Wu
Bin Shao
41
1
0
06 Jun 2024
Topological Neural Networks go Persistent, Equivariant, and Continuous
Topological Neural Networks go Persistent, Equivariant, and Continuous
Yogesh Verma
Amauri H Souza
Vikas K. Garg
AI4CE
46
4
0
05 Jun 2024
Machine learning Hubbard parameters with equivariant neural networks
Machine learning Hubbard parameters with equivariant neural networks
M. Uhrin
A. Zadoks
Luca Binci
Nicola Marzari
I. Timrov
33
6
0
04 Jun 2024
Neural Thermodynamic Integration: Free Energies from Energy-based
  Diffusion Models
Neural Thermodynamic Integration: Free Energies from Energy-based Diffusion Models
Bálint Máté
François Fleuret
Tristan Bereau
DiffM
46
2
0
04 Jun 2024
A Space Group Symmetry Informed Network for O(3) Equivariant Crystal
  Tensor Prediction
A Space Group Symmetry Informed Network for O(3) Equivariant Crystal Tensor Prediction
Keqiang Yan
Alexandra Saxton
Xiaofeng Qian
Xiaoning Qian
Shuiwang Ji
42
6
0
03 Jun 2024
Neural Polarization: Toward Electron Density for Molecules by Extending
  Equivariant Networks
Neural Polarization: Toward Electron Density for Molecules by Extending Equivariant Networks
Bumju Kwak
Jeonghee Jo
53
0
0
01 Jun 2024
Predicting solvation free energies with an implicit solvent machine learning potential
Predicting solvation free energies with an implicit solvent machine learning potential
Sebastien Röcken
A. F. Burnet
Julija Zavadlav
AI4Cl
AI4CE
74
3
0
31 May 2024
Neural Isometries: Taming Transformations for Equivariant ML
Neural Isometries: Taming Transformations for Equivariant ML
Thomas W. Mitchel
Michael Taylor
Vincent Sitzmann
30
0
0
29 May 2024
A Recipe for Charge Density Prediction
A Recipe for Charge Density Prediction
Xiang Fu
Andrew S. Rosen
Kyle Bystrom
Rui Wang
Albert Musaelian
Boris Kozinsky
Tess E. Smidt
Tommi Jaakkola
53
5
0
29 May 2024
SE3Set: Harnessing equivariant hypergraph neural networks for molecular
  representation learning
SE3Set: Harnessing equivariant hypergraph neural networks for molecular representation learning
Hongfei Wu
Lijun Wu
Guoqing Liu
Zhirong Liu
Bin Shao
Zun Wang
43
1
0
26 May 2024
E(n) Equivariant Topological Neural Networks
E(n) Equivariant Topological Neural Networks
Claudio Battiloro
Ege Karaismailoglu
Mauricio Tec
George Dasoulas
Michelle Audirac
Francesca Dominici
55
5
0
24 May 2024
Higher-Rank Irreducible Cartesian Tensors for Equivariant Message
  Passing
Higher-Rank Irreducible Cartesian Tensors for Equivariant Message Passing
Viktor Zaverkin
Francesco Alesiani
Takashi Maruyama
Federico Errica
Henrik Christiansen
Makoto Takamoto
Nicolas Weber
Mathias Niepert
49
5
0
23 May 2024
Accurate Learning of Equivariant Quantum Systems from a Single Ground
  State
Accurate Learning of Equivariant Quantum Systems from a Single Ground State
Stepán Smíd
Roberto Bondesan
43
0
0
20 May 2024
Response Matching for generating materials and molecules
Response Matching for generating materials and molecules
Bingqing Cheng
DiffM
32
1
0
15 May 2024
Dielectric Tensor Prediction for Inorganic Materials Using Latent
  Information from Preferred Potential
Dielectric Tensor Prediction for Inorganic Materials Using Latent Information from Preferred Potential
Zetian Mao
Wenwen Li
Jethro Tan
38
2
0
15 May 2024
Overcoming systematic softening in universal machine learning
  interatomic potentials by fine-tuning
Overcoming systematic softening in universal machine learning interatomic potentials by fine-tuning
Bowen Deng
Yunyeong Choi
Peichen Zhong
Janosh Riebesell
Shashwat Anand
Zhuohan Li
KyuJung Jun
Kristin A. Persson
Gerbrand Ceder
AI4CE
40
16
0
11 May 2024
Multi-task learning for molecular electronic structure approaching
  coupled-cluster accuracy
Multi-task learning for molecular electronic structure approaching coupled-cluster accuracy
Hao Tang
Brian Xiao
Wenhao He
Pero Subasic
A. Harutyunyan
Yao Wang
Fang Liu
Haowei Xu
Ju Li
34
1
0
09 May 2024
AdsorbDiff: Adsorbate Placement via Conditional Denoising Diffusion
AdsorbDiff: Adsorbate Placement via Conditional Denoising Diffusion
Adeesh Kolluru
John R. Kitchin
DiffM
47
4
0
07 May 2024
Graph as Point Set
Graph as Point Set
Xiyuan Wang
Pan Li
Muhan Zhang
GNN
3DPC
PINN
44
4
0
05 May 2024
FeNNol: an Efficient and Flexible Library for Building
  Force-field-enhanced Neural Network Potentials
FeNNol: an Efficient and Flexible Library for Building Force-field-enhanced Neural Network Potentials
Thomas Plé
Olivier Adjoua
Louis Lagardère
Jean‐Philip Piquemal
34
8
0
02 May 2024
HEroBM: a deep equivariant graph neural network for universal
  backmapping from coarse-grained to all-atom representations
HEroBM: a deep equivariant graph neural network for universal backmapping from coarse-grained to all-atom representations
Daniele Angioletti
S. Raniolo
V. Limongelli
29
0
0
25 Apr 2024
Molecular relaxation by reverse diffusion with time step prediction
Molecular relaxation by reverse diffusion with time step prediction
Khaled Kahouli
Stefaan S. P. Hessmann
Klaus-Robert Muller
Shinichi Nakajima
Stefan Gugler
Niklas W. A. Gebauer
DiffM
41
5
0
16 Apr 2024
Interpolation and differentiation of alchemical degrees of freedom in
  machine learning interatomic potentials
Interpolation and differentiation of alchemical degrees of freedom in machine learning interatomic potentials
Juno Nam
Rafael Gómez-Bombarelli
AI4CE
40
4
0
16 Apr 2024
How Deep Networks Learn Sparse and Hierarchical Data: the Sparse Random
  Hierarchy Model
How Deep Networks Learn Sparse and Hierarchical Data: the Sparse Random Hierarchy Model
Umberto M. Tomasini
M. Wyart
BDL
41
7
0
16 Apr 2024
VN-EGNN: E(3)-Equivariant Graph Neural Networks with Virtual Nodes
  Enhance Protein Binding Site Identification
VN-EGNN: E(3)-Equivariant Graph Neural Networks with Virtual Nodes Enhance Protein Binding Site Identification
Florian Sestak
Lisa Schneckenreiter
Johannes Brandstetter
Sepp Hochreiter
Andreas Mayr
G. Klambauer
39
7
0
10 Apr 2024
Equivariant graph convolutional neural networks for the representation
  of homogenized anisotropic microstructural mechanical response
Equivariant graph convolutional neural networks for the representation of homogenized anisotropic microstructural mechanical response
Ravi G. Patel
C. Safta
Reese E. Jones
AI4CE
37
1
0
05 Apr 2024
Grappa -- A Machine Learned Molecular Mechanics Force Field
Grappa -- A Machine Learned Molecular Mechanics Force Field
Leif Seute
Eric Hartmann
Jan Stühmer
Frauke Gräter
29
3
0
25 Mar 2024
Complete and Efficient Graph Transformers for Crystal Material Property
  Prediction
Complete and Efficient Graph Transformers for Crystal Material Property Prediction
Keqiang Yan
Cong Fu
Xiaofeng Qian
Xiaoning Qian
Shuiwang Ji
46
19
0
18 Mar 2024
Generalizing Denoising to Non-Equilibrium Structures Improves
  Equivariant Force Fields
Generalizing Denoising to Non-Equilibrium Structures Improves Equivariant Force Fields
Yi-Lun Liao
Tess E. Smidt
Abhishek Das
DiffM
AI4CE
40
12
0
14 Mar 2024
Accurate Crystal Structure Prediction of New 2D Hybrid Organic Inorganic
  Perovskites
Accurate Crystal Structure Prediction of New 2D Hybrid Organic Inorganic Perovskites
Nima Karimitari
William J. Baldwin
Evan W. Muller
Zachary J. L. Bare
W. J. Kennedy
Gábor Csányi
Christopher Sutton
33
5
0
11 Mar 2024
Bridging Text and Molecule: A Survey on Multimodal Frameworks for
  Molecule
Bridging Text and Molecule: A Survey on Multimodal Frameworks for Molecule
Yi Xiao
Xiangxin Zhou
Qiang Liu
Liang Wang
AI4CE
32
3
0
07 Mar 2024
Deciphering diffuse scattering with machine learning and the equivariant
  foundation model: The case of molten FeO
Deciphering diffuse scattering with machine learning and the equivariant foundation model: The case of molten FeO
Ganesh Sivaraman
C. Benmore
AI4CE
21
0
0
01 Mar 2024
A Survey of Geometric Graph Neural Networks: Data Structures, Models and Applications
A Survey of Geometric Graph Neural Networks: Data Structures, Models and Applications
Jiaqi Han
Jiacheng Cen
Liming Wu
Zongzhao Li
Xiangzhe Kong
...
Zhewei Wei
Deli Zhao
Yu Rong
Wenbing Huang
Wenbing Huang
AI4CE
34
20
0
01 Mar 2024
TorchMD-Net 2.0: Fast Neural Network Potentials for Molecular
  Simulations
TorchMD-Net 2.0: Fast Neural Network Potentials for Molecular Simulations
Raúl P. Peláez
Guillem Simeon
Raimondas Galvelis
Antonio Mirarchi
Peter K. Eastman
Stefan Doerr
Philipp Thölke
T. Markland
Gianni De Fabritiis
AI4CE
34
12
0
27 Feb 2024
Equivariant Frames and the Impossibility of Continuous Canonicalization
Equivariant Frames and the Impossibility of Continuous Canonicalization
Nadav Dym
Hannah Lawrence
Jonathan W. Siegel
41
17
0
25 Feb 2024
Pretraining Strategy for Neural Potentials
Pretraining Strategy for Neural Potentials
Zehua Zhang
Zijie Li
A. Farimani
AI4CE
44
0
0
24 Feb 2024
On normalization-equivariance properties of supervised and unsupervised
  denoising methods: a survey
On normalization-equivariance properties of supervised and unsupervised denoising methods: a survey
Sébastien Herbreteau
Charles Kervrann
OOD
43
0
0
23 Feb 2024
PARCv2: Physics-aware Recurrent Convolutional Neural Networks for
  Spatiotemporal Dynamics Modeling
PARCv2: Physics-aware Recurrent Convolutional Neural Networks for Spatiotemporal Dynamics Modeling
Phong C. H. Nguyen
Xinlun Cheng
Shahab Azarfar
P. Seshadri
Y. Nguyen
Munho Kim
Sanghun Choi
H. Udaykumar
Stephen Seung-Yeob Baek
AI4CE
PINN
40
1
0
19 Feb 2024
Universal Physics Transformers: A Framework For Efficiently Scaling Neural Operators
Universal Physics Transformers: A Framework For Efficiently Scaling Neural Operators
Benedikt Alkin
Andreas Fürst
Simon Schmid
Lukas Gruber
Markus Holzleitner
Johannes Brandstetter
PINN
AI4CE
48
8
0
19 Feb 2024
Clifford Group Equivariant Simplicial Message Passing Networks
Clifford Group Equivariant Simplicial Message Passing Networks
Cong Liu
David Ruhe
Floor Eijkelboom
Patrick Forré
27
13
0
15 Feb 2024
Cartesian atomic cluster expansion for machine learning interatomic
  potentials
Cartesian atomic cluster expansion for machine learning interatomic potentials
Bingqing Cheng
42
30
0
12 Feb 2024
Neural SPH: Improved Neural Modeling of Lagrangian Fluid Dynamics
Neural SPH: Improved Neural Modeling of Lagrangian Fluid Dynamics
Artur P. Toshev
Jonas A. Erbesdobler
Nikolaus A. Adams
Johannes Brandstetter
AI4CE
46
4
0
09 Feb 2024
On the Completeness of Invariant Geometric Deep Learning Models
On the Completeness of Invariant Geometric Deep Learning Models
Zian Li
Xiyuan Wang
Shijia Kang
Muhan Zhang
36
2
0
07 Feb 2024
Reducing the Cost of Quantum Chemical Data By Backpropagating Through
  Density Functional Theory
Reducing the Cost of Quantum Chemical Data By Backpropagating Through Density Functional Theory
Alexander Mathiasen
Hatem Helal
Paul Balanca
Adam Krzywaniak
Ali Parviz
Frederik Hvilshoj
Bla.zej Banaszewski
Carlo Luschi
Andrew William Fitzgibbon
43
3
0
06 Feb 2024
Equivariant Symmetry Breaking Sets
Equivariant Symmetry Breaking Sets
YuQing Xie
Tess E. Smidt
25
4
0
05 Feb 2024
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