◍wovepaper
SearchResearchersInstitutions
Sign in
researcher

David Holzmüller

INRIA Paris

29 papers hereh-index 14829 citations33 works total

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

author position
  • sole author3
  • first author5
  • middle author19
  • last author1

Across the 28 of 29 papers where every author was matched, so the position is known.

fields
  • cs.LG14
  • stat.ML9
  • physics.comp-ph4
  • cs.CG1
  • cs.DS1
affiliations
  • INRIA Paris
Homepage

identity via Semantic Scholar / OpenAlex

activity
20172026
most citedUncertainty-biased molecular dynamics for learning uniformly accurate interatomic potentials

51 citations · 228 across the 23 of their papers we have counts for

collaborators
Showing 2021Show all

1 paper · 1 filter

physics.comp-ph2021★ 41 cited

Fast and Sample-Efficient Interatomic Neural Network Potentials for Molecules and Materials Based on Gaussian Moments

Viktor Zaverkin, David Holzmüller, Ingo Steinwart +1

Artificial neural networks (NNs) are one of the most frequently used machine learning approaches to construct interatomic potentials and enable efficient large-scale atomistic simu…

◍wovepaper

Papers, researchers and institutions, woven together.

Explore
  • Search
  • Researchers
  • Institutions
Account
  • Library
  • Chat
Data
  • arXiv.org
  • Semantic Scholar
  • OpenAlex
  • Latest RSS
AboutContactPrivacyDevelopersllms.txtopenapi.json
Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.