Xu, Keyulu

9 publications

ICML 2021 GraphNorm: A Principled Approach to Accelerating Graph Neural Network Training Tianle Cai, Shengjie Luo, Keyulu Xu, Di He, Tie-Yan Liu, Liwei Wang

NeurIPS 2021 How Does a Neural Network's Architecture Impact Its Robustness to Noisy Labels? Jingling Li, Mozhi Zhang, Keyulu Xu, John Dickerson, Jimmy Ba

ICLR 2021 How Neural Networks Extrapolate: From Feedforward to Graph Neural Networks Keyulu Xu, Mozhi Zhang, Jingling Li, Simon Shaolei Du, Ken-Ichi Kawarabayashi, Stefanie Jegelka

ICML 2021 Information Obfuscation of Graph Neural Networks Peiyuan Liao, Han Zhao, Keyulu Xu, Tommi Jaakkola, Geoffrey J. Gordon, Stefanie Jegelka, Ruslan Salakhutdinov

ICML 2021 Optimization of Graph Neural Networks: Implicit Acceleration by Skip Connections and More Depth Keyulu Xu, Mozhi Zhang, Stefanie Jegelka, Kenji Kawaguchi

ICLR 2020 What Can Neural Networks Reason About? Keyulu Xu, Jingling Li, Mozhi Zhang, Simon S. Du, Ken-ichi Kawarabayashi, Stefanie Jegelka

NeurIPS 2019 Graph Neural Tangent Kernel: Fusing Graph Neural Networks with Graph Kernels Simon S Du, Kangcheng Hou, Ruslan Salakhutdinov, Barnabas Poczos, Ruosong Wang, Keyulu Xu

ICLR 2019 How Powerful Are Graph Neural Networks? Keyulu Xu, Weihua Hu, Jure Leskovec, Stefanie Jegelka

ICML 2018 Representation Learning on Graphs with Jumping Knowledge Networks Keyulu Xu, Chengtao Li, Yonglong Tian, Tomohiro Sonobe, Ken-ichi Kawarabayashi, Stefanie Jegelka