Xiaofeng Qian

According to our database, Xiaofeng Qian authored at least 14 papers between 2021 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2025

Tensor Decomposition Networks for Fast Machine Learning Interatomic Potential Computations.

Yuchao Lin, Cong Fu, Zachary Krueger, Haiyang Yu, Maho Nakata, Jianwen Xie, Emine Küçükbenli, Xiaofeng Qian, Shuiwang Ji

CoRR, July, 2025

Augmenting Molecular Graphs with Geometries via Machine Learning Interatomic Potentials.

Cong Fu, Yuchao Lin, Zachary Krueger, Haiyang Yu, Maho Nakata, Jianwen Xie, Emine Küçükbenli, Xiaofeng Qian, Shuiwang Ji

CoRR, July, 2025

Efficient Prediction of SO(3)-Equivariant Hamiltonian Matrices via SO(2) Local Frames.

Haiyang Yu, Yuchao Lin, Xuan Zhang, Xiaofeng Qian, Shuiwang Ji

CoRR, June, 2025

Toward Greater Autonomy in Materials Discovery Agents: Unifying Planning, Physics, and Scientists.

Lianhao Zhou, Hongyi Ling, Keqiang Yan, Kaiji Zhao, Xiaoning Qian, Raymundo Arróyave, Xiaofeng Qian, Shuiwang Ji

CoRR, June, 2025

A Materials Foundation Model via Hybrid Invariant-Equivariant Architectures.

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

CoRR, March, 2025

Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems.

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

Found. Trends Mach. Learn., 2025

2024

Invariant Tokenization of Crystalline Materials for Language Model Enabled Generation.

Keqiang Yan, Xiner Li, Hongyi Ling, Kenna Ashen, Carl Edwards, Raymundo Arróyave, Marinka Zitnik, Heng Ji, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

A Space Group Symmetry Informed Network for O(3) Equivariant Crystal Tensor Prediction.

Keqiang Yan, Alexandra Saxton, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Complete and Efficient Graph Transformers for Crystal Material Property Prediction.

Keqiang Yan, Cong Fu, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Knowledge-driven learning, optimization, and experimental design under uncertainty for materials discovery.

Xiaoning Qian, Byung-Jun Yoon, Raymundo Arróyave, Xiaofeng Qian, Edward R. Dougherty

Patterns, November, 2023

QH9: A Quantum Hamiltonian Prediction Benchmark for QM9 Molecules.

Haiyang Yu, Meng Liu, Youzhi Luo, Alex Strasser, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Efficient and Equivariant Graph Networks for Predicting Quantum Hamiltonian.

Haiyang Yu, Zhao Xu, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji

Proceedings of the International Conference on Machine Learning, 2023

2022

Graph neural network for Hamiltonian-based material property prediction.

Hexin Bai, Peng Chu, Jeng-Yuan Tsai, Nathan Wilson, Xiaofeng Qian, Qimin Yan, Haibin Ling

Neural Comput. Appl., 2022

2021

Physics-constrained Automatic Feature Engineering for Predictive Modeling in Materials Science.

Ziyu Xiang, Mingzhou Fan, Guillermo Vázquez Tovar, William Trehern, Byung-Jun Yoon, Xiaofeng Qian, Raymundo Arróyave, Xiaoning Qian

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021