How Powerful are Graph Neural Networks? K Xu, W Hu, J Leskovec, S Jegelka International Conference on Learning Representations, 2019 | 7220 | 2019 |

Representation learning on graphs with jumping knowledge networks K Xu, C Li, Y Tian, T Sonobe, K Kawarabayashi, S Jegelka International Conference on Machine Learning, 2018 | 1980 | 2018 |

How neural networks extrapolate: From feedforward to graph neural networks K Xu, M Zhang, J Li, SS Du, K Kawarabayashi, S Jegelka International Conference on Learning Representations, 2021 | 294 | 2021 |

Graph neural tangent kernel: Fusing graph neural networks with graph kernels SS Du, K Hou, B Póczos, R Salakhutdinov, R Wang, K Xu Advances in Neural Information Processing Systems, 2019 | 257 | 2019 |

What Can Neural Networks Reason About? K Xu, J Li, M Zhang, SS Du, K Kawarabayashi, S Jegelka International Conference on Learning Representations, 2020 | 253 | 2020 |

Graphnorm: A principled approach to accelerating graph neural network training T Cai, S Luo, K Xu, D He, T Liu, L Wang International Conference on Machine Learning, 2021 | 134 | 2021 |

How powerful are graph neural networks? arXiv 2018 K Xu, W Hu, J Leskovec, S Jegelka arXiv preprint arXiv:1810.00826, 1810 | 79 | 1810 |

Optimization of Graph Neural Networks: Implicit Acceleration by Skip Connections and More Depth K Xu, M Zhang, S Jegelka, K Kawaguchi International Conference on Machine Learning, 2021 | 74 | 2021 |

How powerful are graph neural networks?(2018) K Xu, W Hu, J Leskovec, S Jegelka arXiv preprint arXiv:1810.00826, 1810 | 53 | 1810 |

Are Girls Neko or Sh\= ojo? Cross-Lingual Alignment of Non-Isomorphic Embeddings with Iterative Normalization M Zhang, K Xu, K Kawarabayashi, S Jegelka, J Boyd-Graber Association for Computational Linguistics, 2019 | 50 | 2019 |

Information obfuscation of graph neural networks P Liao, H Zhao, K Xu, T Jaakkola, GJ Gordon, S Jegelka, R Salakhutdinov International conference on machine learning, 6600-6610, 2021 | 49* | 2021 |

How does a Neural Network's Architecture Impact its Robustness to Noisy Labels? J Li, M Zhang, K Xu, J Dickerson, J Ba Advances in Neural Information Processing Systems 34, 9788-9803, 2021 | 29* | 2021 |

Distributional adversarial networks C Li, D Alvarez-Melis, K Xu, S Jegelka, S Sra International Conference on Learning Representations workshop track, 2018 | 28 | 2018 |

Generating random spanning trees via fast matrix multiplication NJA Harvey, K Xu LATIN 2016: Theoretical Informatics: 12th Latin American Symposium, Ensenada …, 2016 | 12 | 2016 |

Modeling Intelligence via Graph Neural Networks K Xu Massachusetts Institute of Technology, 2021 | | 2021 |