most citedAllegro-Legato: Scalable, Fast, and Robust Neural-Network Quantum Molecular Dynamics via Sharpness-Aware Minimization

3 citations · 3 across the 2 of their papers we have counts for

collaborators

2 papers

cond-mat.mtrl-sci2026

Upscaling DFT-trained machine-learning interatomic potential toward Quantum Monte Carlo accuracy: Sulfur-vacancy migration in monolayer MoS as a testbed

Adam Hložný, Ján Brndiar, Ye Luo +1

We designed a procedure to train a machine learning interatomic potential (MLIP) at benchmark-quality quantum Monte Carlo (QMC) accuracy. To avoid the complexities of high-quality…

cs.DC2023★ 3 cited

Allegro-Legato: Scalable, Fast, and Robust Neural-Network Quantum Molecular Dynamics via Sharpness-Aware Minimization

Hikaru Ibayashi, Taufeq Mohammed Razakh, Liqiu Yang +8

Neural-network quantum molecular dynamics (NNQMD) simulations based on machine learning are revolutionizing atomistic simulations of materials by providing quantum-mechanical accur…