596 citations · 758 across the 5 of their papers we have counts for
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physics.chem-ph2023★ 132 cited
DPA-2: a large atomic model as a multi-task learner
Duo Zhang, Xinzijian Liu, Xiangyu Zhang +40
The rapid advancements in artificial intelligence (AI) are catalyzing transformative changes in atomic modeling, simulation, and design. AI-driven potential energy models have demo…
physics.chem-ph2023★ 596 cited
DeePMD-kit v2: A software package for Deep Potential models
Jinzhe Zeng, Duo Zhang, Denghui Lu +44
DeePMD-kit is a powerful open-source software package that facilitates molecular dynamics simulations using machine learning potentials (MLP) known as Deep Potential (DP) models. T…
physics.chem-ph2022★ 27 cited
DPA-1: Pretraining of Attention-based Deep Potential Model for Molecular Simulation
Duo Zhang, Hangrui Bi, Fu-Zhi Dai +3
Machine learning assisted modeling of the inter-atomic potential energy surface (PES) is revolutionizing the field of molecular simulation. With the accumulation of high-quality el…