Han Wang

Orcid: 0000-0001-5623-1148

Affiliations:
  • Institute of Applied Physics and Computational Mathematics, Beijing, China
  • CAEP Software Center for High Performance Numerical Simulation, Beijing, China
  • Peking University, School of Mathematical Sciences, LMAM, Beijing, China (former)


According to our database1, Han Wang authored at least 20 papers between 2007 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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Links

Online presence:

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Bibliography

2024
Dflow, a Python framework for constructing cloud-native AI-for-Science workflows.
CoRR, 2024

2023
DeePKS-kit: A package for developing machine learning-based chemically accurate energy and density functional models.
Comput. Phys. Commun., 2023

2022
Efficient sampling of high-dimensional free energy landscapes using adaptive reinforced dynamics.
Nat. Comput. Sci., 2022

A deep variational free energy approach to dense hydrogen.
CoRR, 2022

DPA-1: Pretraining of Attention-based Deep Potential Model for Molecular Simulation.
CoRR, 2022

DeePKS+ABACUS as a Bridge between Expensive Quantum Mechanical Models and Machine Learning Potentials.
CoRR, 2022

Extending the limit of molecular dynamics with ab initio accuracy to 10 billion atoms.
CoRR, 2022

Extending the limit of molecular dynamics with <i>ab initio</i> accuracy to 10 billion atoms.
Proceedings of the PPoPP '22: 27th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, Seoul, Republic of Korea, April 2, 2022

2021
86 PFLOPS Deep Potential Molecular Dynamics simulation of 100 million atoms with <i>ab initio</i> accuracy.
Comput. Phys. Commun., 2021

2020
DP-GEN: A concurrent learning platform for the generation of reliable deep learning based potential energy models.
Comput. Phys. Commun., 2020

DeePKS: a comprehensive data-driven approach towards chemically accurate density functional theory.
CoRR, 2020

86 PFLOPS Deep Potential Molecular Dynamics simulation of 100 million atoms with ab initio accuracy.
CoRR, 2020

Pushing the limit of molecular dynamics with <i>ab initio</i> accuracy to 100 million atoms with machine learning.
Proceedings of the International Conference for High Performance Computing, 2020

2018
DeePMD-kit: A deep learning package for many-body potential energy representation and molecular dynamics.
Comput. Phys. Commun., 2018

Active Learning of Uniformly Accurate Inter-atomic Potentials for Materials Simulation.
CoRR, 2018

End-to-end Symmetry Preserving Inter-atomic Potential Energy Model for Finite and Extended Systems.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2017
Parallel 3-dim fast Fourier transforms with load balancing of the plane waves.
Comput. Phys. Commun., 2017

Reinforced dynamics for enhanced sampling in large atomic and molecular systems. I. Basic Methodology.
CoRR, 2017

Deep Potential Molecular Dynamics: a scalable model with the accuracy of quantum mechanics.
CoRR, 2017

2007
An efficient adaptive mesh redistribution method for a non-linear Dirac equation.
J. Comput. Phys., 2007


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