1 citations · 1 across the 2 of their papers we have counts for
2 papers
cond-mat.mtrl-sci2025
Composable and adaptive design of machine learning interatomic potentials guided by Fisher-information analysis
Weishi Wang, Mark K. Transtrum, Vincenzo Lordi +2
An adaptive physics-inspired model design strategy for machine-learning interatomic potentials (MLIPs) is proposed. This strategy relies on iterative reconfigurations of composite…
stat.AP2022★ 1 cited
GAN-MC: a Variance Reduction Tool for Derivatives Pricing
Weishi Wang
We propose a parameter-free model for estimating the price or valuation of financial derivatives like options, forwards and futures using non-supervised learning networks and Monte…