| Adaptive universal generalized pagerank graph neural network E Chien, J Peng, P Li, O Milenkovic International Conference on Learning Representations, 2021 | 749 | 2021 |
| Distance encoding: Design provably more powerful neural networks for graph representation learning P Li, Y Wang, H Wang, J Leskovec Advances in Neural Information Processing Systems 33, 4465-4478, 2020 | 358* | 2020 |
| Adversarial graph augmentation to improve graph contrastive learning S Suresh, P Li, C Hao, J Neville Advances in Neural Information Processing Systems 34, 15920-15933, 2021 | 331 | 2021 |
| Labeling trick: A theory of using graph neural networks for multi-node representation learning M Zhang, P Li, Y Xia, K Wang, L Jin Advances in Neural Information Processing Systems 34, 9061-9073, 2021 | 260* | 2021 |
| Inductive representation learning in temporal networks via causal anonymous walks Y Wang, YY Chang, Y Liu, J Leskovec, P Li International Conference on Learning Representations, 2021 | 248 | 2021 |
| Graph information bottleneck T Wu, H Ren, P Li, J Leskovec Advances in Neural Information Processing Systems 33, 20437-20448, 2020 | 236 | 2020 |
| Interpretable and Generalizable Graph Learning via Stochastic Attention Mechanism S Miao, M Liu, P Li International Conference on Machine Learning, 15524-15543, 2022 | 179 | 2022 |
| Inhomogeneous hypergraph clustering with applications P Li, O Milenkovic Advances in Neural Information Processing Systems, 2017 | 175 | 2017 |
| Nested Graph Neural Networks M Zhang, P Li Advances in Neural Information Processing Systems, 2021 | 159 | 2021 |
| Breaking the Limit of Graph Neural Networks by Improving the Assortativity of Graphs with Local Mixing Patterns S Suresh, V Budde, J Neville, P Li, J Ma Proceedings of the ACM SIGKDD Conference on Knowledge Discovery & Data Mining, 2021 | 132 | 2021 |
| Equivariant and Stable Positional Encoding for More Powerful Graph Neural Networks H Wang, H Yin, M Zhang, P Li International Conference on Learning Representations, 2022 | 114 | 2022 |
| Submodular hypergraphs: p-laplacians, cheeger inequalities and spectral clustering P Li, O Milenkovic International Conference on Machine Learning, 3014-3023, 2018 | 110 | 2018 |
| Conditional structure generation through graph variational generative adversarial nets C Yang, P Zhuang, W Shi, A Luu, P Li Advances in Neural Information Processing Systems, 2019 | 109 | 2019 |
| Motif and hypergraph correlation clustering P Li, GJ Puleo, O Milenkovic IEEE Transactions on Information Theory 66 (5), 3065-3078, 2019 | 96* | 2019 |
| On positional and structural node features for graph neural networks on non-attributed graphs H Cui, Z Lu, P Li, C Yang Proceedings of the 31st ACM International Conference on Information …, 2022 | 80 | 2022 |
| Better trigger inversion optimization in backdoor scanning G Tao, G Shen, Y Liu, S An, Q Xu, S Ma, P Li, X Zhang Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 75 | 2022 |
| Optimizing generalized pagerank methods for seed-expansion community detection P Li, E Chien, O Milenkovic Advances in Neural Information Processing Systems, 2019 | 69 | 2019 |
| MSTREAM: Fast anomaly detection in multi-aspect streams S Bhatia, A Jain, P Li, R Kumar, B Hooi Proceedings of the Web Conference, 2021 | 66 | 2021 |
| Graph Auto-Encoder Via Neighborhood Wasserstein Reconstruction M Tang, C Yang, P Li International Conference on Learning Representations, 2022 | 63 | 2022 |
| Applications and techniques for fast machine learning in science AMC Deiana, N Tran, J Agar, M Blott, G Di Guglielmo, J Duarte, P Harris, ... Frontiers in big Data 5, 2022 | 62 | 2022 |
Olgica MilenkovicUniversity of IllinoisVerified email at illinois.edu
