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Transfer learning for chemically accurate interatomic neural network
  potentials

Transfer learning for chemically accurate interatomic neural network potentials

7 December 2022
Viktor Zaverkin
David Holzmüller
Luca Bonfirraro
Johannes Kastner
ArXivPDFHTML

Papers citing "Transfer learning for chemically accurate interatomic neural network potentials"

4 / 4 papers shown
Title
Optimal Invariant Bases for Atomistic Machine Learning
Optimal Invariant Bases for Atomistic Machine Learning
Alice Allen
Emily Shinkle
Roxana Bujack
Nicholas Lubbers
37
0
0
30 Mar 2025
Physics-Informed Weakly Supervised Learning for Interatomic Potentials
Physics-Informed Weakly Supervised Learning for Interatomic Potentials
Makoto Takamoto
Viktor Zaverkin
Mathias Niepert
AI4CE
55
0
0
23 Jul 2024
Pre-Train Your Loss: Easy Bayesian Transfer Learning with Informative
  Priors
Pre-Train Your Loss: Easy Bayesian Transfer Learning with Informative Priors
Ravid Shwartz-Ziv
Micah Goldblum
Hossein Souri
Sanyam Kapoor
Chen Zhu
Yann LeCun
A. Wilson
UQCV
BDL
56
43
0
20 May 2022
Gaussian Moments as Physically Inspired Molecular Descriptors for
  Accurate and Scalable Machine Learning Potentials
Gaussian Moments as Physically Inspired Molecular Descriptors for Accurate and Scalable Machine Learning Potentials
Viktor Zaverkin
Johannes Kastner
32
67
0
15 Sep 2021
1