| How Powerful are Graph Neural Networks? K Xu, W Hu, J Leskovec, S Jegelka International Conference on Learning Representations, 2019 | 2725 | 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 | 885 | 2018 |
| What Can Neural Networks Reason About? K Xu, J Li, M Zhang, SS Du, K Kawarabayashi, S Jegelka International Conference on Learning Representations, 2020 | 129 | 2020 |
| 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 | 124 | 2019 |
| 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 | 95 | 2021 |
| 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 | 43 | 2021 |
| Distributional adversarial networks C Li, D Alvarez-Melis, K Xu, S Jegelka, S Sra International Conference on Learning Representations workshop track, 2018 | 35* | 2018 |
| 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 | 30 | 2019 |
| 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 | 16 | 2021 |
| Generating random spanning trees via fast matrix multiplication NJA Harvey, K Xu LATIN 2016: Theoretical Informatics, 522-535, 2016 | 12 | 2016 |
| 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 | 10 | 2021 |
| Noisy labels can induce good representations J Li, M Zhang, K Xu, JP Dickerson, J Ba Advances in Neural Information Processing Systems, 2021 | 9 | 2021 |
| Graph Adversarial Networks: Protecting Information against Adversarial Attacks P Liao, H Zhao, K Xu, T Jaakkola, G Gordon, S Jegelka, R Salakhutdinov International Conference on Machine Learning, 2021 | 6 | 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, 2021 | 1 | 2021 |
| Modeling Intelligence via Graph Neural Networks K Xu Massachusetts Institute of Technology, 2021 | | 2021 |
