| Adaptive universal generalized pagerank graph neural network E Chien, J Peng, P Li, O Milenkovic International Conference on Learning Representations, 2021 | 1186 | 2021 |
| 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 | 500 | 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 | 492 | 2020 |
| 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 | 403 | 2021 |
| Graph information bottleneck T Wu, H Ren, P Li, J Leskovec Advances in Neural Information Processing Systems 33, 20437-20448, 2020 | 391 | 2020 |
| 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 | 380* | 2021 |
| Interpretable and Generalizable Graph Learning via Stochastic Attention Mechanism S Miao, M Liu, P Li International Conference on Machine Learning, 15524-15543, 2022 | 338 | 2022 |
| Nested Graph Neural Networks M Zhang, P Li Advances in Neural Information Processing Systems, 2021 | 237 | 2021 |
| Inhomogeneous hypergraph clustering with applications P Li, O Milenkovic Advances in Neural Information Processing Systems, 2017 | 204 | 2017 |
| 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 | 191 | 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 | 185 | 2022 |
| Submodular hypergraphs: p-laplacians, cheeger inequalities and spectral clustering P Li, O Milenkovic International Conference on Machine Learning, 3014-3023, 2018 | 134 | 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 | 133 | 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 | 129 | 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 | 111 | 2022 |
| GAD-NR: Graph Anomaly Detection via Neighborhood Reconstruction A Roy, J Shu, J Li, C Yang, O Elshocht, J Smeets, P Li The 17th ACM International Conference on Web Search and Data Mining, 2024 | 110 | 2024 |
| Motif and hypergraph correlation clustering P Li, GJ Puleo, O Milenkovic IEEE Transactions on Information Theory 66 (5), 3065-3078, 2019 | 103* | 2019 |
| Equivariant Hypergraph Diffusion Neural Operators P Wang, S Yang, Y Liu, Z Wang, P Li International Conference on Learning Representations, 2023 | 99 | 2023 |
| Neighborhood-aware Scalable Temporal Network Representation Learning Y Luo, P Li Learning on Graphs (best paper award), 2022 | 98 | 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 | 96 | 2022 |
Eli ChienAssistant Professor at National Taiwan UniversityVerified email at gatech.edu
