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Neural Polarization: Toward Electron Density for Molecules by Extending Equivariant Networks

arXiv 2406.00441 ↗First posted 1 Jun 2024physics.chem-ph cs.AI cs.LGcited by 0

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Abstract (arXiv)

Recent SO(3)-equivariant models embedded a molecule as a set of single atoms fixed in the three-dimensional space, which is analogous to a ball-and-stick view. This perspective provides a concise view of atom arrangements, however, the surrounding electron density cannot be represented and its polarization effects may be underestimated. To overcome this limitation, we propose textitNeural Polarization, a novel method extending equivariant network by embedding each atom as a pair of fixed and moving points. Motivated by density functional theory, Neural Polarization represents molecules as a space-filling view which includes an electron density, in contrast with a ball-and-stick view. Neural Polarization can flexibly be applied to most type of existing equivariant models. We showed that Neural Polarization can improve prediction performances of existing models over a wide range of targets. Finally, we verified that our method can improve the expressiveness and equivariance in terms of mathematical aspects.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 26 of its 78 references that are in the map. First posted on arXiv 1 Jun 2024.

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References · 26

  1. 2017Neural Message Passing for Quantum Chemistrycited by 3,460
  2. 2021E(n) Equivariant Graph Neural Networkscited by 951
  3. 2018Tensor field networks: Rotation- and translation-equivariant neural networks for 3D point cloudscited by 735
  4. 2021E(3)-Equivariant Graph Neural Networks for Data-Efficient and Accurate Interatomic Potentialscited by 701
  5. 2022Equivariant Diffusion for Molecule Generation in 3Dcited by 666
  6. 2020SE(3)-Transformers: 3D Roto-Translation Equivariant Attention Networkscited by 602
  7. 2017SchNet: A continuous-filter convolutional neural network for modeling quantum interactionscited by 569
  8. 2022MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fieldscited by 467
  9. 2021Equivariant message passing for the prediction of tensorial properties and molecular spectracited by 438
  10. 2021GemNet: Universal Directional Graph Neural Networks for Moleculescited by 342
  11. 2018Neural Relational Inference for Interacting Systemscited by 339
  12. 2021Vector Neurons: A General Framework for SO(3)-Equivariant Networkscited by 304
14 more
  1. 2019Cormorant: Covariant Molecular Neural Networkscited by 262
  2. 2022Equiformer: Equivariant Graph Attention Transformer for 3D Atomistic Graphscited by 258
  3. 2020Fast and Uncertainty-Aware Directional Message Passing for Non-Equilibrium Moleculescited by 254
  4. 2021Geometric and Physical Quantities Improve E(3) Equivariant Message Passingcited by 225
  5. 2022TorchMD-NET: Equivariant Transformers for Neural Network based Molecular Potentialscited by 179
  6. 2021SpookyNet: Learning Force Fields with Electronic Degrees of Freedom and Nonlocal Effectscited by 103
  7. 2021Provably efficient machine learning for quantum many-body problemscited by 91
  8. 2019Unifying machine learning and quantum chemistry -- a deep neural network for molecular wavefunctionscited by 73
  9. 2016By-passing the Kohn-Sham equations with machine learningcited by 65
  10. 2022So3krates: Equivariant attention for interactions on arbitrary length-scales in molecular systemscited by 39
  11. 2023QH9: A Quantum Hamiltonian Prediction Benchmark for QM9 Moleculescited by 26
  12. 2021Equivariant graph neural networks for fast electron density estimation of molecules, liquids, and solidscited by 24
  13. 2023Beyond MD17: the reactive xxMD datasetcited by 6
  14. 2022Putting Density Functional Theory to the Test in Machine-Learning-Accelerated Materials Discoverycited by 3

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