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Unified theory of atom-centered representations and message-passing
  machine-learning schemes
v1v2v3 (latest)

Unified theory of atom-centered representations and message-passing machine-learning schemes

Journal of Chemical Physics (JCP), 2022
3 February 2022
Jigyasa Nigam
Sergey Pozdnyakov
Guillaume Fraux
Michele Ceriotti
    AI4CE
ArXiv (abs)PDFHTML

Papers citing "Unified theory of atom-centered representations and message-passing machine-learning schemes"

12 / 12 papers shown
Representing spherical tensors with scalar-based machine-learning models
Representing spherical tensors with scalar-based machine-learning models
Michelangelo Domina
Filippo Bigi
Paolo Pegolo
Michele Ceriotti
460
3
0
08 May 2025
The dark side of the forces: assessing non-conservative force models for atomistic machine learning
The dark side of the forces: assessing non-conservative force models for atomistic machine learning
Filippo Bigi
Marcel F. Langer
Michele Ceriotti
AI4CE
1.0K
37
0
16 Dec 2024
Probing the effects of broken symmetries in machine learning
Probing the effects of broken symmetries in machine learning
Marcel F. Langer
Sergey Pozdnyakov
Michele Ceriotti
AI4CE
281
21
0
25 Jun 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
163
2
0
25 Apr 2024
Enabling Efficient Equivariant Operations in the Fourier Basis via Gaunt
  Tensor Products
Enabling Efficient Equivariant Operations in the Fourier Basis via Gaunt Tensor Products
Shengjie Luo
Tianlang Chen
Aditi S. Krishnapriyan
240
40
0
18 Jan 2024
Electronic excited states from physically-constrained machine learning
Electronic excited states from physically-constrained machine learningACS Central Science (ACS Cent. Sci.), 2023
Edoardo Cignoni
Divya Suman
Jigyasa Nigam
Lorenzo Cupellini
B. Mennucci
Michele Ceriotti
361
27
0
01 Nov 2023
Evaluation of the MACE Force Field Architecture: from Medicinal
  Chemistry to Materials Science
Evaluation of the MACE Force Field Architecture: from Medicinal Chemistry to Materials ScienceJournal of Chemical Physics (JCP), 2023
D. P. Kovács
Ilyes Batatia
E. Arany
Gábor Csányi
AI4CE
337
157
0
23 May 2023
Wigner kernels: body-ordered equivariant machine learning without a
  basis
Wigner kernels: body-ordered equivariant machine learning without a basisJournal of Chemical Physics (JCP), 2023
Filippo Bigi
Sergey Pozdnyakov
Michele Ceriotti
201
20
0
07 Mar 2023
Completeness of Atomic Structure Representations
Completeness of Atomic Structure RepresentationsAPL Machine Learning (AML), 2023
M. J. Willatt
Sergey Pozdnyakov
Christoph Ortner
Michele Ceriotti
432
19
0
28 Feb 2023
A smooth basis for atomistic machine learning
A smooth basis for atomistic machine learningJournal of Chemical Physics (JCP), 2022
Filippo Bigi
Kevin K. Huguenin-Dumittan
Michele Ceriotti
D. Manolopoulos
270
9
0
05 Sep 2022
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 FieldsNeural Information Processing Systems (NeurIPS), 2022
Ilyes Batatia
D. P. Kovács
G. Simm
Christoph Ortner
Gábor Csányi
370
907
0
15 Jun 2022
The Design Space of E(3)-Equivariant Atom-Centered Interatomic
  Potentials
The Design Space of E(3)-Equivariant Atom-Centered Interatomic Potentials
Ilyes Batatia
Simon L. Batzner
D. P. Kovács
Albert Musaelian
G. Simm
R. Drautz
Christoph Ortner
Boris Kozinsky
Gábor Csányi
403
300
0
13 May 2022
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