most citedKohn-Sham accuracy from orbital-free density functional theory via -machine learning

1 citations · 1 across the 3 of their papers we have counts for

collaborators

3 papers

cs.AI2024

CasFT: Future Trend Modeling for Information Popularity Prediction with Dynamic Cues-Driven Diffusion Models

Xin Jing, Yichen Jing, Yuhuan Lu +3

The rapid spread of diverse information on online social platforms has prompted both academia and industry to realize the importance of predicting content popularity, which could b…

physics.comp-ph2024

On-the-fly machine learned force fields for the study of warm dense matter: application to diffusion and viscosity of CH

Shashikant Kumar, Xin Jing, John E. Pask +1

We develop a framework for on-the-fly machine learned force field (MLFF) molecular dynamics (MD) simulations of warm dense matter (WDM). In particular, we employ an MLFF scheme bas…

physics.chem-ph2023★ 1 cited

Kohn-Sham accuracy from orbital-free density functional theory via -machine learning

Shashikant Kumar, Xin Jing, John E. Pask +2

We present a -machine learning model for obtaining Kohn-Sham accuracy from orbital-free density functional theory (DFT) calculations. In particular, we employ a machine learned…