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Junhan Chang

Showing results (1-10 of 8) with videos related to

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Nature Computational Science|January 4, 2024
Efficient sampling of high-dimensional free energy landscapes using adaptive reinforced dynamicsDongdong Wang, Yanze Wang, Junhan Chang, et al.
Journal of Chemical Information and Modeling|May 28, 2026
Efficient and Precise Force Field Optimization for Biomolecules Using DPA-3Junhan Chang, Zhe Xu, Duo Zhang, et al.
Journal of Chemical Theory and Computation|August 17, 2023
DMFF: An Open-Source Automatic Differentiable Platform for Molecular Force Field Development and Molecular Dynamics SimulationXinyan Wang, Jichen Li, Lan Yang, et al.
The Journal of Physical Chemistry. A|August 14, 2020
A Perspective on Deep Learning for Molecular Modeling and SimulationsJun Zhang, Yao-Kun Lei, Zhen Zhang, et al.
Nature Chemical Biology|July 14, 2025
Protein β-O-glucosylation by Legionella LtpM through short consensus sequons G-T/S and S-GWei Li, Ling Gao, Shiyong Cui, et al.
Npj Computational Materials|August 25, 2025
DPA-2: a large atomic model as a multi-task learnerDuo Zhang, Xinzijian Liu, Xiangyu Zhang, et al.
Journal of Chemical Theory and Computation|May 2, 2025
DeePMD-kit v3: A Multiple-Backend Framework for Machine Learning PotentialsJinzhe Zeng, Duo Zhang, Anyang Peng, et al.
The Journal of Chemical Physics|August 1, 2023
DeePMD-kit v2: A software package for deep potential modelsJinzhe Zeng, Duo Zhang, Denghui Lu, et al.
Pageof 1

Showing results (1-10 of 8) with videos related to

Sort By:
Pageof 1
Nature Computational Science|January 4, 2024
Efficient sampling of high-dimensional free energy landscapes using adaptive reinforced dynamicsDongdong Wang, Yanze Wang, Junhan Chang, et al.
Journal of Chemical Information and Modeling|May 28, 2026
Efficient and Precise Force Field Optimization for Biomolecules Using DPA-3Junhan Chang, Zhe Xu, Duo Zhang, et al.
Journal of Chemical Theory and Computation|August 17, 2023
DMFF: An Open-Source Automatic Differentiable Platform for Molecular Force Field Development and Molecular Dynamics SimulationXinyan Wang, Jichen Li, Lan Yang, et al.
The Journal of Physical Chemistry. A|August 14, 2020
A Perspective on Deep Learning for Molecular Modeling and SimulationsJun Zhang, Yao-Kun Lei, Zhen Zhang, et al.
Nature Chemical Biology|July 14, 2025
Protein β-O-glucosylation by Legionella LtpM through short consensus sequons G-T/S and S-GWei Li, Ling Gao, Shiyong Cui, et al.
Npj Computational Materials|August 25, 2025
DPA-2: a large atomic model as a multi-task learnerDuo Zhang, Xinzijian Liu, Xiangyu Zhang, et al.
Journal of Chemical Theory and Computation|May 2, 2025
DeePMD-kit v3: A Multiple-Backend Framework for Machine Learning PotentialsJinzhe Zeng, Duo Zhang, Anyang Peng, et al.
The Journal of Chemical Physics|August 1, 2023
DeePMD-kit v2: A software package for deep potential modelsJinzhe Zeng, Duo Zhang, Denghui Lu, et al.
Pageof 1