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2303.04124
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Wigner kernels: body-ordered equivariant machine learning without a basis
7 March 2023
Filippo Bigi
Sergey Pozdnyakov
Michele Ceriotti
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Papers citing
"Wigner kernels: body-ordered equivariant machine learning without a basis"
9 / 9 papers shown
Title
Representing spherical tensors with scalar-based machine-learning models
Michelangelo Domina
Filippo Bigi
Paolo Pegolo
Michele Ceriotti
43
0
0
08 May 2025
Data Fusion of Deep Learned Molecular Embeddings for Property Prediction
Robert Appleton
Brian C Barnes
Alejandro Strachan
FedML
AI4CE
32
0
0
09 Apr 2025
HydraScreen: A Generalizable Structure-Based Deep Learning Approach to Drug Discovery
Alvaro Prat
Hisham Abdel-Aty
Gintautas Kamuntavicius
Tanya Paquet
P. Norvaisas
Piero Gasparotto
Roy Tal
18
2
0
22 Sep 2023
Smooth, exact rotational symmetrization for deep learning on point clouds
Sergey Pozdnyakov
Michele Ceriotti
3DPC
30
25
0
30 May 2023
Evaluation of the MACE Force Field Architecture: from Medicinal Chemistry to Materials Science
D. P. Kovács
Ilyes Batatia
E. Arany
Gábor Csányi
AI4CE
19
81
0
23 May 2023
Tensor-reduced atomic density representations
James P. Darby
D. P. Kovács
Ilyes Batatia
M. A. Caro
G. Hart
Christoph Ortner
Gábor Csányi
44
32
0
02 Oct 2022
Gaussian Moments as Physically Inspired Molecular Descriptors for Accurate and Scalable Machine Learning Potentials
Viktor Zaverkin
Johannes Kastner
32
67
0
15 Sep 2021
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
M. Bronstein
Joan Bruna
Taco S. Cohen
Petar Velivcković
GNN
172
1,100
0
27 Apr 2021
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
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