Han Wang
Orcid: 0000-0001-5623-1148Affiliations:
- 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:
Collaborative distances:
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Bibliography
2024
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
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
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
J. Comput. Phys., 2007