Wang, Yangkun

6 publications

JMLR 2025 Implicit vs Unfolded Graph Neural Networks Yongyi Yang, Tang Liu, Yangkun Wang, Zengfeng Huang, David Wipf

ICLR 2022 Does Your Graph Need a Confidence Boost? Convergent Boosted Smoothing on Graphs with Tabular Node Features Jiuhai Chen, Jonas Mueller, Vassilis N. Ioannidis, Soji Adeshina, Yangkun Wang, Tom Goldstein, David Wipf

ICLR 2022 Inductive Relation Prediction Using Analogy Subgraph Embeddings Jiarui Jin, Yangkun Wang, Kounianhua Du, Weinan Zhang, Zheng Zhang, David Wipf, Yong Yu, Quan Gan

NeurIPS 2022 Learning Enhanced Representation for Tabular Data via Neighborhood Propagation Kounianhua Du, Weinan Zhang, Ruiwen Zhou, Yangkun Wang, Xilong Zhao, Jiarui Jin, Quan Gan, Zheng Zhang, David P Wipf

ICLR 2022 Why Propagate Alone? Parallel Use of Labels and Features on Graphs Yangkun Wang, Jiarui Jin, Weinan Zhang, Yang Yongyi, Jiuhai Chen, Quan Gan, Yong Yu, Zheng Zhang, Zengfeng Huang, David Wipf

ICML 2021 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