| Beyond homophily in graph neural networks: Current limitations and effective designs J Zhu, Y Yan, L Zhao, M Heimann, L Akoglu, D Koutra Advances in neural information processing systems 33, 7793-7804, 2020 | 1306 | 2020 |
| Pairnorm: Tackling oversmoothing in gnns L Zhao, L Akoglu ICLR 2020, 2019 | 712 | 2019 |
| From stars to subgraphs: Uplifting any GNN with local structure awareness L Zhao, W Jin, L Akoglu, N Shah ICLR 2022, 2021 | 225 | 2021 |
| Graph condensation for graph neural networks W Jin, L Zhao, S Zhang, Y Liu, J Tang, N Shah ICLR 2022, 2021 | 222 | 2021 |
| Sign and basis invariant networks for spectral graph representation learning D Lim, J Robinson, L Zhao, T Smidt ICLR 2023, 2022 | 211 | 2022 |
| Graph unrolling networks: Interpretable neural networks for graph signal denoising S Chen, YC Eldar, L Zhao IEEE Transactions on Signal Processing 69, 3699-3713, 2021 | 102 | 2021 |
| Chain of draft: Thinking faster by writing less S Xu, W Xie, L Zhao, P He arXiv preprint arXiv:2502.18600, 2025 | 87 | 2025 |
| On using classification datasets to evaluate graph outlier detection: Peculiar observations and new insights L Zhao, L Akoglu Big Data 11 (3), 151-180, 2023 | 81 | 2023 |
| Generalizing graph neural networks beyond homophily J Zhu, Y Yan, L Zhao, M Heimann, L Akoglu, D Koutra arXiv preprint arXiv:2006.11468, 2020 | 44 | 2020 |
| A quest for structure: Jointly learning the graph structure and semi-supervised classification X Wu*, L Zhao*, L Akoglu Proceedings of the 27th ACM international conference on information and …, 2018 | 42 | 2018 |
| Hyperparameter sensitivity in deep outlier detection: Analysis and a scalable hyper-ensemble solution X Ding, L Zhao, L Akoglu NeurIPS 2022, 2022 | 31 | 2022 |
| Graph Anomaly Detection with Unsupervised GNNs L Zhao, S Sawlani, A Srinivasan, L Akoglu ICDM 2022 short, 2022 | 29 | 2022 |
| Heterophily and graph neural networks: Past, present and future J Zhu, Y Yan, M Heimann, L Zhao, L Akoglu, D Koutra IEEE Data Engineering Bulletin, 2023 | 27 | 2023 |
| A Practical, Progressively-Expressive GNN L Zhao, L Härtel, N Shah, L Akoglu NeurIPS 2022, 2022 | 26 | 2022 |
| Improving and Unifying Discrete&Continuous-time Discrete Denoising Diffusion L Zhao*, X Ding*, L Yu, L Akoglu arXiv preprint arXiv:2402.03701, 2024 | 15* | 2024 |
| On the expressive power of spectral invariant graph neural networks B Zhang, L Zhao, H Maron arXiv preprint arXiv:2406.04336, 2024 | 12 | 2024 |
| Pard: Permutation-Invariant Autoregressive Diffusion for Graph Generation L Zhao, X Ding, L Akoglu NeurIPS 2024, 2024 | 10 | 2024 |
| Fast attributed graph embedding via density of states S Sawlani, L Zhao, L Akoglu 2021 IEEE International Conference on Data Mining (ICDM), 559-568, 2021 | 10 | 2021 |
| DSV: an alignment validation loss for self-supervised outlier model selection J Yoo, Y Zhao, L Zhao, L Akoglu Joint European Conference on Machine Learning and Knowledge Discovery in …, 2023 | 8 | 2023 |
| End-to-end augmentation hyperparameter tuning for self-supervised anomaly detection J Yoo, L Zhao, L Akoglu arXiv preprint arXiv:2306.12033, 2023 | 6 | 2023 |
Leman AkogluAssociate Professor, Carnegie Mellon UniversityVerified email at andrew.cmu.edu
Danai KoutraUniversity of Michigan, Ann ArborVerified email at umich.edu
Neil ShahResearch Scientist at SnapVerified email at snap.com
Wei JinAssistant Professor, Emory UniversityVerified email at emory.edu
Haggai MaronAssistant Professor at the Technion, Research Scientist at NVIDIA ResearchVerified email at technion.ac.il
Saurabh SawlaniAmira LearningVerified email at amiralearning.com
Siheng ChenShanghai Jiao Tong UniversityVerified email at sjtu.edu.cn