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researcher

E. Weinan

79 papers hereh-index 5819.2k citations208 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author26
  • middle author18
  • last author32

Across the 76 of 79 papers where every author was matched, so the position is known.

fields
  • cs.LG21
  • physics.comp-ph17
  • physics.chem-ph7
  • math.NA6
  • stat.ML6
  • cond-mat.mtrl-sci4
same name
  • E. Weinan — 23 papers, h 7
  • E. Weinan — 14 papers, h 7
  • E. Weinan — 5 papers, h 3
  • E. Weinan — 4 papers, h 5
  • E. Weinan — 4 papers, h 2

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
19992023
most citedDeep Potential Molecular Dynamics: a scalable model with the accuracy of quantum mechanics

2.3k citations · 10.3k across the 79 of their papers we have counts for

collaborators
Showing 2018 · physics.comp-phShow all

3 papers · 2 filters

physics.comp-ph2018★ 519 cited

Active Learning of Uniformly Accurate Inter-atomic Potentials for Materials Simulation

Linfeng Zhang, De-Ye Lin, Han Wang +2

An active learning procedure called Deep Potential Generator (DP-GEN) is proposed for the construction of accurate and transferable machine learning-based models of the potential e…

physics.comp-ph2018★ 217 cited

Solving Many-Electron Schrödinger Equation Using Deep Neural Networks

Jiequn Han, Linfeng Zhang, Weinan E

We introduce a new family of trial wave-functions based on deep neural networks to solve the many-electron Schrödinger equation. The Pauli exclusion principle is dealt with explici…

physics.comp-ph2018★ 157 cited

End-to-end Symmetry Preserving Inter-atomic Potential Energy Model for Finite and Extended Systems

Linfeng Zhang, Jiequn Han, Han Wang +3

Machine learning models are changing the paradigm of molecular modeling, which is a fundamental tool for material science, chemistry, and computational biology. Of particular inter…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.