Zun Wang

Senior Researcher

Publications

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Infusing Self-Consistency into Density Functional Theory Hamiltonian Prediction via Deep Equilibrium Models

Zun Wang, Chang Liu, Nianlong Zou, He Zhang, Xinran wei, Lin Huang, Lijun Wu, Bin Shao

NeurIPS 2024 | June 2024

DOI Publication Publication

Self-Consistency Training for Density-Functional-Theory Hamiltonian Prediction

He Zhang, Chang Liu, Zun Wang, Xinran wei, Siyuan Liu, Nanning Zheng, Bin Shao, Tie-Yan Liu

ICML 2024 | March 2024

DOI Publication Publication

Enhancing geometric representations for molecules with equivariant vector-scalar interactive message passing

Yusong Wang, Tong Wang, Shaoning Li, Xinheng He, Mingyu Li, Zun Wang, Nanning Zheng, Bin Shao, Tie-Yan Liu

Nature Communications | January 2024, Vol 15(313)

Publication
Efficiently incorporating quintuple interactions into geometric deep learning force fields

Zun Wang, Guoqing Liu, Yichi Zhou, Tong Wang, Bin Shao

NeurIPS 2023 | October 2023

Publication

AI2BMD: efficient characterization of protein dynamics with ab initio accuracy

Tong Wang, Xinheng He, Mingyu Li, Yusong Wang, Zun Wang, Shaoning Li, Bin Shao, Tie-Yan Liu

July 2023

Preprint

Improving machine learning force fields for molecular dynamics simulations with fine-grained force metrics

Zun Wang, Hongfei Wu, Lixin Sun, Xinheng He, Zhirong Liu, Bin Shao, Tong Wang, Tie-Yan Liu

The Journal of Chemical Physics | July 2023, Vol 159(3)

Cover Story

Publication

Long-Short-Range Message-Passing: A Physics-Informed Framework to Capture Non-Local Interaction for Scalable Molecular Dynamics Simulation

Yunyang Li, Yusong Wang, Lin Huang, Han Yang, Xinran wei, Jia Zhang, Tong Wang, Zun Wang, Bin Shao, Tie-Yan Liu

April 2023

Preprint
ViSNet: a scalable and accurate geometric deep learning potential for molecular dynamics simulation

Yusong Wang, Shaoning Li, Xinheng He, Mingyu Li, Zun Wang, Nanning Zheng, Bin Shao, Tong Wang, Tie-Yan Liu

October 2022

Preprint

Infusing Self-Consistency into Density Functional Theory Hamiltonian Prediction via Deep Equilibrium Models

Zun Wang, Chang Liu, Nianlong Zou, He Zhang, Xinran wei, Lin Huang, Lijun Wu, Bin Shao

NeurIPS 2024 | June 2024

DOI Publication Publication

Self-Consistency Training for Density-Functional-Theory Hamiltonian Prediction

He Zhang, Chang Liu, Zun Wang, Xinran wei, Siyuan Liu, Nanning Zheng, Bin Shao, Tie-Yan Liu

ICML 2024 | March 2024

DOI Publication Publication

Enhancing geometric representations for molecules with equivariant vector-scalar interactive message passing

Yusong Wang, Tong Wang, Shaoning Li, Xinheng He, Mingyu Li, Zun Wang, Nanning Zheng, Bin Shao, Tie-Yan Liu

Nature Communications | January 2024, Vol 15(313)

Publication

Efficiently incorporating quintuple interactions into geometric deep learning force fields

Zun Wang, Guoqing Liu, Yichi Zhou, Tong Wang, Bin Shao

NeurIPS 2023 | October 2023

Publication

AI2BMD: efficient characterization of protein dynamics with ab initio accuracy

Tong Wang, Xinheng He, Mingyu Li, Yusong Wang, Zun Wang, Shaoning Li, Bin Shao, Tie-Yan Liu

July 2023

Preprint

Improving machine learning force fields for molecular dynamics simulations with fine-grained force metrics

Zun Wang, Hongfei Wu, Lixin Sun, Xinheng He, Zhirong Liu, Bin Shao, Tong Wang, Tie-Yan Liu

The Journal of Chemical Physics | July 2023, Vol 159(3)

Cover Story

Publication

Long-Short-Range Message-Passing: A Physics-Informed Framework to Capture Non-Local Interaction for Scalable Molecular Dynamics Simulation

Yunyang Li, Yusong Wang, Lin Huang, Han Yang, Xinran wei, Jia Zhang, Tong Wang, Zun Wang, Bin Shao, Tie-Yan Liu

April 2023

Preprint

ViSNet: a scalable and accurate geometric deep learning potential for molecular dynamics simulation

Yusong Wang, Shaoning Li, Xinheng He, Mingyu Li, Zun Wang, Nanning Zheng, Bin Shao, Tong Wang, Tie-Yan Liu

October 2022

Preprint
AI2BMD: efficient characterization of protein dynamics with ab initio accuracy

Tong Wang, Xinheng He, Mingyu Li, Yusong Wang, Zun Wang, Shaoning Li, Bin Shao, Tie-Yan Liu

July 2023

Preprint

Long-Short-Range Message-Passing: A Physics-Informed Framework to Capture Non-Local Interaction for Scalable Molecular Dynamics Simulation

Yunyang Li, Yusong Wang, Lin Huang, Han Yang, Xinran wei, Jia Zhang, Tong Wang, Zun Wang, Bin Shao, Tie-Yan Liu

April 2023

Preprint

ViSNet: a scalable and accurate geometric deep learning potential for molecular dynamics simulation

Yusong Wang, Shaoning Li, Xinheng He, Mingyu Li, Zun Wang, Nanning Zheng, Bin Shao, Tong Wang, Tie-Yan Liu

October 2022

Preprint
AI2BMD: efficient characterization of protein dynamics with ab initio accuracy

Tong Wang, Xinheng He, Mingyu Li, Yusong Wang, Zun Wang, Shaoning Li, Bin Shao, Tie-Yan Liu

July 2023

Preprint

Improving machine learning force fields for molecular dynamics simulations with fine-grained force metrics

Zun Wang, Hongfei Wu, Lixin Sun, Xinheng He, Zhirong Liu, Bin Shao, Tong Wang, Tie-Yan Liu

The Journal of Chemical Physics | July 2023, Vol 159(3)

Cover Story

Publication

Long-Short-Range Message-Passing: A Physics-Informed Framework to Capture Non-Local Interaction for Scalable Molecular Dynamics Simulation

Yunyang Li, Yusong Wang, Lin Huang, Han Yang, Xinran wei, Jia Zhang, Tong Wang, Zun Wang, Bin Shao, Tie-Yan Liu

April 2023

Preprint

ViSNet: a scalable and accurate geometric deep learning potential for molecular dynamics simulation

Yusong Wang, Shaoning Li, Xinheng He, Mingyu Li, Zun Wang, Nanning Zheng, Bin Shao, Tong Wang, Tie-Yan Liu

October 2022

Preprint

Infusing Self-Consistency into Density Functional Theory Hamiltonian Prediction via Deep Equilibrium Models

Zun Wang, Chang Liu, Nianlong Zou, He Zhang, Xinran wei, Lin Huang, Lijun Wu, Bin Shao

NeurIPS 2024 | June 2024

DOI Publication Publication

Self-Consistency Training for Density-Functional-Theory Hamiltonian Prediction

He Zhang, Chang Liu, Zun Wang, Xinran wei, Siyuan Liu, Nanning Zheng, Bin Shao, Tie-Yan Liu

ICML 2024 | March 2024

DOI Publication Publication

Efficiently incorporating quintuple interactions into geometric deep learning force fields

Zun Wang, Guoqing Liu, Yichi Zhou, Tong Wang, Bin Shao

NeurIPS 2023 | October 2023

Publication
Enhancing geometric representations for molecules with equivariant vector-scalar interactive message passing

Yusong Wang, Tong Wang, Shaoning Li, Xinheng He, Mingyu Li, Zun Wang, Nanning Zheng, Bin Shao, Tie-Yan Liu

Nature Communications | January 2024, Vol 15(313)

Publication

AI2BMD: efficient characterization of protein dynamics with ab initio accuracy

Tong Wang, Xinheng He, Mingyu Li, Yusong Wang, Zun Wang, Shaoning Li, Bin Shao, Tie-Yan Liu

July 2023

Preprint

Improving machine learning force fields for molecular dynamics simulations with fine-grained force metrics

Zun Wang, Hongfei Wu, Lixin Sun, Xinheng He, Zhirong Liu, Bin Shao, Tong Wang, Tie-Yan Liu

The Journal of Chemical Physics | July 2023, Vol 159(3)

Cover Story

Publication

Long-Short-Range Message-Passing: A Physics-Informed Framework to Capture Non-Local Interaction for Scalable Molecular Dynamics Simulation

Yunyang Li, Yusong Wang, Lin Huang, Han Yang, Xinran wei, Jia Zhang, Tong Wang, Zun Wang, Bin Shao, Tie-Yan Liu

April 2023

Preprint

ViSNet: a scalable and accurate geometric deep learning potential for molecular dynamics simulation

Yusong Wang, Shaoning Li, Xinheng He, Mingyu Li, Zun Wang, Nanning Zheng, Bin Shao, Tong Wang, Tie-Yan Liu

October 2022

Preprint

Zun Wang

Publications

Infusing Self-Consistency into Density Functional Theory Hamiltonian Prediction via Deep Equilibrium Models

Self-Consistency Training for Density-Functional-Theory Hamiltonian Prediction

Enhancing geometric representations for molecules with equivariant vector-scalar interactive message passing

Efficiently incorporating quintuple interactions into geometric deep learning force fields

AI2BMD: efficient characterization of protein dynamics with ab initio accuracy

Improving machine learning force fields for molecular dynamics simulations with fine-grained force metrics

Long-Short-Range Message-Passing: A Physics-Informed Framework to Capture Non-Local Interaction for Scalable Molecular Dynamics Simulation

ViSNet: a scalable and accurate geometric deep learning potential for molecular dynamics simulation

Infusing Self-Consistency into Density Functional Theory Hamiltonian Prediction via Deep Equilibrium Models

Self-Consistency Training for Density-Functional-Theory Hamiltonian Prediction

Enhancing geometric representations for molecules with equivariant vector-scalar interactive message passing

Efficiently incorporating quintuple interactions into geometric deep learning force fields

AI2BMD: efficient characterization of protein dynamics with ab initio accuracy

Improving machine learning force fields for molecular dynamics simulations with fine-grained force metrics

Long-Short-Range Message-Passing: A Physics-Informed Framework to Capture Non-Local Interaction for Scalable Molecular Dynamics Simulation

ViSNet: a scalable and accurate geometric deep learning potential for molecular dynamics simulation

AI2BMD: efficient characterization of protein dynamics with ab initio accuracy

Long-Short-Range Message-Passing: A Physics-Informed Framework to Capture Non-Local Interaction for Scalable Molecular Dynamics Simulation

ViSNet: a scalable and accurate geometric deep learning potential for molecular dynamics simulation

AI2BMD: efficient characterization of protein dynamics with ab initio accuracy

Improving machine learning force fields for molecular dynamics simulations with fine-grained force metrics

Long-Short-Range Message-Passing: A Physics-Informed Framework to Capture Non-Local Interaction for Scalable Molecular Dynamics Simulation

ViSNet: a scalable and accurate geometric deep learning potential for molecular dynamics simulation

Infusing Self-Consistency into Density Functional Theory Hamiltonian Prediction via Deep Equilibrium Models

Self-Consistency Training for Density-Functional-Theory Hamiltonian Prediction

Efficiently incorporating quintuple interactions into geometric deep learning force fields

Enhancing geometric representations for molecules with equivariant vector-scalar interactive message passing

AI2BMD: efficient characterization of protein dynamics with ab initio accuracy

Improving machine learning force fields for molecular dynamics simulations with fine-grained force metrics

Long-Short-Range Message-Passing: A Physics-Informed Framework to Capture Non-Local Interaction for Scalable Molecular Dynamics Simulation

ViSNet: a scalable and accurate geometric deep learning potential for molecular dynamics simulation

Contact Zun Wang

Microsoft Research AI for Science

Zun Wang

Publications

Publications by Year

2024

2023

2022

Publications by Research Area

Artificial intelligence

Algorithms

Medical, health and genomics

Publications by Type

Inproceedings (Conference)

Article (Journal)