Xiaofeng Qian

25 papers A* 6Journal 19
YearRankTypeTitle / Venue / Authors
2026 J jnl
Augmenting Molecular Graphs with Geometries via Machine Learning Interatomic Potentials.
Trans. Mach. Learn. Res.
Cong Fu, Yuchao Lin, Zachary Krueger, Haiyang Yu, Maho Nakata, Jianwen Xie, Emine Küçükbenli, Xiaofeng Qian, Shuiwang Ji
2026 J jnl
Orbital Transformers for Predicting Wavefunctions in Time-Dependent Density Functional Theory.
CoRR
Xuan Zhang, Haiyang Yu, Chengdong Wang, Jacob Helwig, Shuiwang Ji, Xiaofeng Qian
2026 J jnl
Precise bone age assessment via multi-task feature disentanglement and quadruplet ranking.
Neurocomputing
Guoyong Dai, Chen Guo, Tianyu Zhou, Junhao Chen, Yantao Shao, Ruiji Xu, Keji Mao, Xiaofeng Qian
2025 J jnl
A Materials Foundation Model via Hybrid Invariant-Equivariant Architectures.
CoRR
Keqiang Yan, Montgomery Bohde, Andrii Kryvenko, Ziyu Xiang, Kaiji Zhao, Siya Zhu, Saagar Kolachina, Doguhan Saritürk, Jianwen Xie, Raymundo Arróyave, Xiaoning Qian, Xiaofeng Qian, Shuiwang Ji
2025 J jnl
Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems.
Found. Trends Mach. Learn.
Xuan Zhang, Limei Wang, Jacob Helwig, Youzhi Luo, Cong Fu, Yaochen Xie, Meng Liu, Yuchao Lin, Zhao Xu, Keqiang Yan, Keir Adams, Maurice Weiler, Xiner Li, Tianfan Fu, Yucheng Wang, Alex Strasser, Haiyang Yu, Yuqing Xie, Xiang Fu, Shenglong Xu, Yi Liu, Yuanqi Du, Alexandra Saxton, Hongyi Ling, Hannah Lawrence, Hannes Stärk, Shurui Gui, Carl Edwards, Nicholas Gao, Adriana Ladera, Tailin Wu, Elyssa F. Hofgard, Aria Mansouri Tehrani, Rui Wang, Ameya Daigavane, Montgomery Bohde, Jerry Kurtin, Qian Huang, Tuong Phung, Minkai Xu, Chaitanya K. Joshi, Simon V. Mathis, Kamyar Azizzadenesheli, Ada Fang, Alán Aspuru-Guzik, Erik J. Bekkers, Michael M. Bronstein, Marinka Zitnik, Anima Anandkumar, Stefano Ermon, Pietro Liò, Rose Yu, Stephan Günnemann, Jure Leskovec, Heng Ji, Jimeng Sun, Regina Barzilay, Tommi S. Jaakkola, Connor W. Coley, Xiaoning Qian, Xiaofeng Qian, Tess E. Smidt, Shuiwang Ji
2025 J jnl
Augmenting Molecular Graphs with Geometries via Machine Learning Interatomic Potentials.
CoRR
Cong Fu, Yuchao Lin, Zachary Krueger, Haiyang Yu, Maho Nakata, Jianwen Xie, Emine Küçükbenli, Xiaofeng Qian, Shuiwang Ji
2025 J jnl
Autonomous Agents for Scientific Discovery: Orchestrating Scientists, Language, Code, and Physics.
CoRR
Lianhao Zhou, Hongyi Ling, Cong Fu, Yepeng Huang, Michael Sun, Wendi Yu, Xiaoxuan Wang, Xiner Li, Xingyu Su, Junkai Zhang, Xiusi Chen, Chenxing Liang, Xiaofeng Qian, Heng Ji, Wei Wang, Marinka Zitnik, Shuiwang Ji
2025 J jnl
Efficient Prediction of SO(3)-Equivariant Hamiltonian Matrices via SO(2) Local Frames.
CoRR
Haiyang Yu, Yuchao Lin, Xuan Zhang, Xiaofeng Qian, Shuiwang Ji
2025 J jnl
Invariant Tokenization of Crystalline Materials for Language Model Enabled Generation.
CoRR
Keqiang Yan, Xiner Li, Hongyi Ling, Kenna Ashen, Carl Edwards, Raymundo Arróyave, Marinka Zitnik, Heng Ji, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji
2025 J jnl
Tensor Decomposition Networks for Fast Machine Learning Interatomic Potential Computations.
CoRR
Yuchao Lin, Cong Fu, Zachary Krueger, Haiyang Yu, Maho Nakata, Jianwen Xie, Emine Küçükbenli, Xiaofeng Qian, Shuiwang Ji
2025 J jnl
Toward Greater Autonomy in Materials Discovery Agents: Unifying Planning, Physics, and Scientists.
CoRR
Lianhao Zhou, Hongyi Ling, Keqiang Yan, Kaiji Zhao, Xiaoning Qian, Raymundo Arróyave, Xiaofeng Qian, Shuiwang Ji
2024 A* conf
A Space Group Symmetry Informed Network for O(3) Equivariant Crystal Tensor Prediction.
ICML
Keqiang Yan, Alexandra Saxton, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji
2024 J jnl
A Space Group Symmetry Informed Network for O(3) Equivariant Crystal Tensor Prediction.
CoRR
Keqiang Yan, Alexandra Saxton, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji
2024 A* conf
Complete and Efficient Graph Transformers for Crystal Material Property Prediction.
ICLR
Keqiang Yan, Cong Fu, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji
2024 J jnl
Complete and Efficient Graph Transformers for Crystal Material Property Prediction.
CoRR
Keqiang Yan, Cong Fu, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji
2024 A* conf
Invariant Tokenization of Crystalline Materials for Language Model Enabled Generation.
NeurIPS
Keqiang Yan, Xiner Li, Hongyi Ling, Kenna Ashen, Carl Edwards, Raymundo Arróyave, Marinka Zitnik, Heng Ji, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji
2023 J jnl
Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems.
CoRR
Xuan Zhang, Limei Wang, Jacob Helwig, Youzhi Luo, Cong Fu, Yaochen Xie, Meng Liu, Yuchao Lin, Zhao Xu, Keqiang Yan, Keir Adams, Maurice Weiler, Xiner Li, Tianfan Fu, Yucheng Wang, Haiyang Yu, Yuqing Xie, Xiang Fu, Alex Strasser, Shenglong Xu, Yi Liu, Yuanqi Du, Alexandra Saxton, Hongyi Ling, Hannah Lawrence, Hannes Stärk, Shurui Gui, Carl Edwards, Nicholas Gao, Adriana Ladera, Tailin Wu, Elyssa F. Hofgard, Aria Mansouri Tehrani, Rui Wang, Ameya Daigavane, Montgomery Bohde, Jerry Kurtin, Qian Huang, Tuong Phung, Minkai Xu, Chaitanya K. Joshi, Simon V. Mathis, Kamyar Azizzadenesheli, Ada Fang, Alán Aspuru-Guzik, Erik J. Bekkers, Michael M. Bronstein, Marinka Zitnik, Anima Anandkumar, Stefano Ermon, Pietro Liò, Rose Yu, Stephan Günnemann, Jure Leskovec, Heng Ji, Jimeng Sun, Regina Barzilay, Tommi S. Jaakkola, Connor W. Coley, Xiaoning Qian, Xiaofeng Qian, Tess E. Smidt, Shuiwang Ji
2023 A* conf
Efficient and Equivariant Graph Networks for Predicting Quantum Hamiltonian.
ICML
Haiyang Yu, Zhao Xu, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji
2023 J jnl
Efficient and Equivariant Graph Networks for Predicting Quantum Hamiltonian.
CoRR
Haiyang Yu, Zhao Xu, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji
2023 J jnl
Knowledge-driven learning, optimization, and experimental design under uncertainty for materials discovery.
Patterns
Xiaoning Qian, Byung-Jun Yoon, Raymundo Arróyave, Xiaofeng Qian, Edward R. Dougherty
2023 A* conf
QH9: A Quantum Hamiltonian Prediction Benchmark for QM9 Molecules.
NeurIPS
Haiyang Yu, Meng Liu, Youzhi Luo, Alex Strasser, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji
2023 J jnl
QH9: A Quantum Hamiltonian Prediction Benchmark for QM9 Molecules.
CoRR
Haiyang Yu, Meng Liu, Youzhi Luo, Alex Strasser, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji
2022 J jnl
Graph neural network for Hamiltonian-based material property prediction.
Neural Comput. Appl.
Hexin Bai, Peng Chu, Jeng-Yuan Tsai, Nathan Wilson, Xiaofeng Qian, Qimin Yan, Haibin Ling
2021 A* conf
Physics-constrained Automatic Feature Engineering for Predictive Modeling in Materials Science.
AAAI
Ziyu Xiang, Mingzhou Fan, Guillermo Vázquez Tovar, William Trehern, Byung-Jun Yoon, Xiaofeng Qian, Raymundo Arróyave, Xiaoning Qian
2020 J jnl
Graph Neural Network for Hamiltonian-Based Material Property Prediction.
CoRR
Hexin Bai, Peng Chu, Jeng-Yuan Tsai, Nathan Wilson, Xiaofeng Qian, Qimin Yan, Haibin Ling