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ORCIDHaiyang Yu 0005
Person information
- affiliation: Texas A&M University, Department of Computer Science and Engineering, College Station, TX, USA
Other persons with the same name
- Haiyang Yu — disambiguation page
- Haiyang Yu 0001
![[0000-0003-3761-9598]](https://dblp.dagstuhl.de/img/orcid-mark.12x12.png "0000-0003-3761-9598")
— Beijing University of Technology, Data Mining and Security Lab and Beijing Key Laboratory of Trusted Computing, China (and 1 more) - Haiyang Yu 0002 — Beihang University, School of Transportation Science and Engineering, State Key Lab of Intelligent Transportation System, Beijing, China (and 3 more)
- Haiyang Yu 0003 — Alibaba Group, China (and 1 more)
- Haiyang Yu 0004 — Fudan University, School of Computer Science, Shanghai Key Laboratory of Intelligent Information Processing, China
- Haiyang Yu 0006 — University of Calgary, Department of Electrical and Computer Engineering, AB, Canada
- Haiyang Yu 0007 — Troyes University of Technology, Institute Charles Delaunay, France
- Haiyang Yu 0008 — Shizuoka University, Graduate School of Electronic Science and Technology, Japan
- Haiyang Yu 0009 — China Academy of Civil Aviation Science and Technology, Institute of Civil Aviation Development, Beijing, China
- Haiyang Yu 0010 — Dalian University of Technology, Research Center of Information and Control, China
- Haiyang Yu 0011 — Beijing Academy of Agriculture and Forestry Sciences, Beijing Research Center for Information Technology in Agriculture, China
- Haiyang Yu 0012 — Yang Zhou University, China
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2020 – today
- 2025
[j5]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)- [c6]Xingyu Su, Haiyang Yu, Degui Zhi, Shuiwang Ji:
Learning to Discover Regulatory Elements for Gene Expression Prediction. ICLR 2025 - [i16]Xingyu Su, Haiyang Yu, Degui Zhi, Shuiwang Ji:
Learning to Discover Regulatory Elements for Gene Expression Prediction. CoRR abs/2502.13991 (2025) - [i15]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) - [i14]Mouadh Yagoubi, David Danan, Milad Leyli-Abadi, Jocelyn Ahmed Mazari, Jean-Patrick Brunet, Abbas Kabalan, Fabien Casenave, Yuxin Ma, Giovanni Catalani, Jean Fesquet, Jacob Helwig, Xuan Zhang, Haiyang Yu, Xavier Bertrand, Frederic Tost, Michael Bauerheim, Joseph Morlier, Shuiwang Ji:
NeurIPS 2024 ML4CFD Competition: Results and Retrospective Analysis. CoRR abs/2506.08516 (2025) - [i13]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) - [i12]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) - [i11]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) - 2024
- [j4]Zhao Xu, Haiyang Yu, Montgomery Bohde, Shuiwang Ji:
Equivariant Graph Network Approximations of High-Degree Polynomials for Force Field Prediction. Trans. Mach. Learn. Res. 2024 (2024) - [j3]Meng Liu, Haiyang Yu, Shuiwang Ji:
Empowering GNNs via Edge-Aware Weisfeiler-Leman Algorithm. Trans. Mach. Learn. Res. 2024 (2024) - [i10]Zhao Xu, Haiyang Yu, Montgomery Bohde, Shuiwang Ji:
Equivariant Graph Network Approximations of High-Degree Polynomials for Force Field Prediction. CoRR abs/2411.04219 (2024) - [i9]Jacob Helwig, Xuan Zhang, Haiyang Yu, Shuiwang Ji:
A Geometry-Aware Message Passing Neural Network for Modeling Aerodynamics over Airfoils. CoRR abs/2412.09399 (2024) - 2023
- [j2]Hao Yuan, Haiyang Yu, Shurui Gui, Shuiwang Ji:
Explainability in Graph Neural Networks: A Taxonomic Survey. IEEE Trans. Pattern Anal. Mach. Intell. 45(5): 5782-5799 (2023) - [c5]Haiyang Yu, Zhao Xu, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji:
Efficient and Equivariant Graph Networks for Predicting Quantum Hamiltonian. ICML 2023: 40412-40424 - [c4]Haiyang Yu, Meng Liu, Youzhi Luo, Alex Strasser, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji:
QH9: A Quantum Hamiltonian Prediction Benchmark for QM9 Molecules. NeurIPS 2023 - [i8]Haiyang Yu, Zhao Xu, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji:
Efficient and Equivariant Graph Networks for Predicting Quantum Hamiltonian. CoRR abs/2306.04922 (2023) - [i7]Haiyang Yu, Meng Liu, Youzhi Luo, Alex Strasser, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji:
QH9: A Quantum Hamiltonian Prediction Benchmark for QM9 Molecules. CoRR abs/2306.09549 (2023) - [i6]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]Haiyang Yu, Limei Wang, Bokun Wang, Meng Liu, Tianbao Yang, Shuiwang Ji:
GraphFM: Improving Large-Scale GNN Training via Feature Momentum. ICML 2022: 25684-25701 - [c2]Shuiwang Ji, Meng Liu, Yi Liu, Youzhi Luo, Limei Wang, Yaochen Xie, Zhao Xu, Haiyang Yu:
Frontiers of Graph Neural Networks with DIG. KDD 2022: 4796-4797 - [i5]Meng Liu, Haiyang Yu, Shuiwang Ji:
Your Neighbors Are Communicating: Towards Powerful and Scalable Graph Neural Networks. CoRR abs/2206.02059 (2022) - [i4]Haiyang Yu, Limei Wang, Bokun Wang, Meng Liu, Tianbao Yang, Shuiwang Ji:
GraphFM: Improving Large-Scale GNN Training via Feature Momentum. CoRR abs/2206.07161 (2022) - 2021
- [j1]Meng Liu, Youzhi Luo, Limei Wang, Yaochen Xie, Hao Yuan, Shurui Gui, Haiyang Yu, Zhao Xu, Jingtun Zhang, Yi Liu, Keqiang Yan, Haoran Liu, Cong Fu, Bora Oztekin, Xuan Zhang, Shuiwang Ji:
DIG: A Turnkey Library for Diving into Graph Deep Learning Research. J. Mach. Learn. Res. 22: 240:1-240:9 (2021) - [c1]Hao Yuan, Haiyang Yu, Jie Wang, Kang Li, Shuiwang Ji:
On Explainability of Graph Neural Networks via Subgraph Explorations. ICML 2021: 12241-12252 - [i3]Hao Yuan, Haiyang Yu, Jie Wang, Kang Li, Shuiwang Ji:
On Explainability of Graph Neural Networks via Subgraph Explorations. CoRR abs/2102.05152 (2021) - [i2]Meng Liu, Youzhi Luo, Limei Wang, Yaochen Xie, Hao Yuan, Shurui Gui, Zhao Xu, Haiyang Yu, Jingtun Zhang, Yi Liu, Keqiang Yan, Bora Oztekin, Haoran Liu, Xuan Zhang, Cong Fu, Shuiwang Ji:
DIG: A Turnkey Library for Diving into Graph Deep Learning Research. CoRR abs/2103.12608 (2021) - 2020
- [i1]Hao Yuan, Haiyang Yu, Shurui Gui, Shuiwang Ji:
Explainability in Graph Neural Networks: A Taxonomic Survey. CoRR abs/2012.15445 (2020)
Coauthor Index
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