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ORCIDYuchao Lin
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2020 – today
- 2025
[j1]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:
Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems. Found. Trends Mach. Learn. 18(4): 385-912 (2025)- [c7]Xiner Li, Limei Wang, Youzhi Luo, Carl Edwards, Shurui Gui, Yuchao Lin, Heng Ji, Shuiwang Ji:
Geometry Informed Tokenization of Molecules for Language Model Generation. ICML 2025 - [i12]Jacob Helwig, Sai Sreeharsha Adavi, Xuan Zhang, Yuchao Lin, Felix S. Chim, Luke Takeshi Vizzini, Haiyang Yu, Muhammad Hasnain, Saykat Kumar Biswas, John J. Holloway, Narendra Singh, N. K. Anand, Swagnik Guhathakurta, Shuiwang Ji:
A Two-Phase Deep Learning Framework for Adaptive Time-Stepping in High-Speed Flow Modeling. CoRR abs/2506.07969 (2025) - [i11]Haiyang Yu, Yuchao Lin, Xuan Zhang, Xiaofeng Qian, Shuiwang Ji:
Efficient Prediction of SO(3)-Equivariant Hamiltonian Matrices via SO(2) Local Frames. CoRR abs/2506.09398 (2025) - [i10]Cong Fu, Yuchao Lin, Zachary Krueger, Haiyang Yu, Maho Nakata, Jianwen Xie, Emine Küçükbenli, Xiaofeng Qian, Shuiwang Ji:
Augmenting Molecular Graphs with Geometries via Machine Learning Interatomic Potentials. CoRR abs/2507.00407 (2025) - [i9]Yuchao Lin, Cong Fu, Zachary Krueger, Haiyang Yu, Maho Nakata, Jianwen Xie, Emine Küçükbenli, Xiaofeng Qian, Shuiwang Ji:
Tensor Decomposition Networks for Fast Machine Learning Interatomic Potential Computations. CoRR abs/2507.01131 (2025) - [i8]Xingyu Su, Xiner Li, Yuchao Lin, Ziqian Xie, Degui Zhi, Shuiwang Ji:
Language Models for Controllable DNA Sequence Design. CoRR abs/2507.19523 (2025) - 2024
- [c6]Xuan Zhang, Jacob Helwig, Yuchao Lin, Yaochen Xie, Cong Fu, Stephan Wojtowytsch, Shuiwang Ji:
SineNet: Learning Temporal Dynamics in Time-Dependent Partial Differential Equations. ICLR 2024 - [c5]Yuchao Lin, Jacob Helwig, Shurui Gui, Shuiwang Ji:
Equivariance via Minimal Frame Averaging for More Symmetries and Efficiency. ICML 2024 - [i7]Xuan Zhang, Jacob Helwig, Yuchao Lin, Yaochen Xie, Cong Fu, Stephan Wojtowytsch, Shuiwang Ji:
SineNet: Learning Temporal Dynamics in Time-Dependent Partial Differential Equations. CoRR abs/2403.19507 (2024) - [i6]Yuchao Lin, Jacob Helwig, Shurui Gui, Shuiwang Ji:
Equivariance via Minimal Frame Averaging for More Symmetries and Efficiency. CoRR abs/2406.07598 (2024) - [i5]Xiner Li, Limei Wang, Youzhi Luo, Carl Edwards, Shurui Gui, Yuchao Lin, Heng Ji, Shuiwang Ji:
Geometry Informed Tokenization of Molecules for Language Model Generation. CoRR abs/2408.10120 (2024) - 2023
- [c4]Yuchao Lin, Keqiang Yan, Youzhi Luo, Yi Liu, Xiaoning Qian, Shuiwang Ji:
Efficient Approximations of Complete Interatomic Potentials for Crystal Property Prediction. ICML 2023: 21260-21287 - [i4]Yuchao Lin, Keqiang Yan, Youzhi Luo, Yi Liu, Xiaoning Qian, Shuiwang Ji:
Efficient Approximations of Complete Interatomic Potentials for Crystal Property Prediction. CoRR abs/2306.10045 (2023) - [i3]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:
Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems. CoRR abs/2307.08423 (2023) - 2022
- [c3]Yi Liu, Limei Wang, Meng Liu, Yuchao Lin, Xuan Zhang, Bora Oztekin, Shuiwang Ji:
Spherical Message Passing for 3D Molecular Graphs. ICLR 2022 - [c2]Limei Wang, Yi Liu, Yuchao Lin, Haoran Liu, Shuiwang Ji:
ComENet: Towards Complete and Efficient Message Passing for 3D Molecular Graphs. NeurIPS 2022 - [c1]Keqiang Yan, Yi Liu, Yuchao Lin, Shuiwang Ji:
Periodic Graph Transformers for Crystal Material Property Prediction. NeurIPS 2022 - [i2]Limei Wang, Yi Liu, Yuchao Lin, Haoran Liu, Shuiwang Ji:
ComENet: Towards Complete and Efficient Message Passing for 3D Molecular Graphs. CoRR abs/2206.08515 (2022) - [i1]Keqiang Yan, Yi Liu, Yuchao Lin, Shuiwang Ji:
Periodic Graph Transformers for Crystal Material Property Prediction. CoRR abs/2209.11807 (2022)
Coauthor Index
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