Yongyi Yang (杨永祎)
Yongyi is a second-year Ph.D. student at University of Michigan, under the supervision of Prof. Wei Hu. His recent research interests include graph neural networks and the foundations of deep learning.
Before that, Yongyi received Bachelor of Science from Fudan university, under the supervision of Prof. Xipeng Qiu. He also had an internship at Amazon Shanghai AI Lab and has his fortune to be advised by Dr. David Wipf and Prof. Zengfeng Huang.
Besides academic research, Yongyi also harbors a passion in mathematics, Chinese classical literature and XiaoXue. Feel free to contact if you share the same interests.
Contact & Other info
- E-mail: yongyi at umich dot edu
- GitHub: FFTYYY
- WeChat: yyyern
- Google Scholar: Yongyi Yang
Publications and Manuscripts
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Going Beyond Linear Mode Connectivity: The Layerwise Linear Feature Connectivity Zhanpeng Zhou, Yongyi Yang, Xiaojiang Yang, Junchi Yan, Wei Hu
arxiv preprint
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Are Neurons Actually Collapsed? On the Fine-Grained Structure in Neural Representations Yongyi Yang, Jacob Steinhardt, Wei Hu
ICML 2023
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Descent Steps of a Relation-Aware Energy Produce Heterogeneous Graph Neural Networks Hongjoon Ahn,Yongyi Yang, Quan Gan, David Wipf, Taesup Moon
Neurips 2022
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Transformers from an Optimization Perspective Yongyi Yang, Zengfeng Huang, David Wipf
Neurips 2022
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Why Propagate Alone? Parallel Use of Labels and Features on Graphs Yangkun Wang, Jiarui Jin, Weinan Zhang, Yongyi Yang, Jiuhai Chen, Quan Gan, Yong Yu, Zheng Zhang, Zengfeng Huang, David Wipf
ICLR 2022
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Graph Neural Networks Inspired by Classical Iterative Algorithms Yongyi Yang , Tang Liu, Yangkun Wang, Jinjing Zhou, Quan Gan, Zhewei Wei, Zheng Zhang, Zengfeng Huang, David Wipf
ICML 2021, long talk
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Implicit vs Unfolded Graph Neural Networks Yongyi Yang, Yangkun Wang, Tang Liu, Zengfeng Huang, David Wipf
arxiv preprint
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Relation of the Relations: A New Paradigm of the Relation Extraction Problem Zhijing Jin*, Yongyi Yang*, Xipeng Qiu, Zheng Zhang
arxiv preprint
(Last update: 08/30/2023)