Lingxiao Zhao
Cited by
Cited by
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
Pairnorm: Tackling oversmoothing in gnns
L Zhao, L Akoglu
ICLR 2020, 2019
From stars to subgraphs: Uplifting any GNN with local structure awareness
L Zhao, W Jin, L Akoglu, N Shah
ICLR 2022, 2021
Sign and basis invariant networks for spectral graph representation learning
D Lim, J Robinson, L Zhao, T Smidt
ICLR 2023, 2022
Graph condensation for graph neural networks
W Jin, L Zhao, S Zhang, Y Liu, J Tang, N Shah
ICLR 2022, 2021
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
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
Generalizing graph neural networks beyond homophily
J Zhu, Y Yan, L Zhao, M Heimann, L Akoglu, D Koutra
arXiv preprint arXiv:2006.11468, 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
A Practical, Progressively-Expressive GNN
L Zhao, L Härtel, N Shah, L Akoglu
NeurIPS 2022, 2022
Hyperparameter sensitivity in deep outlier detection: Analysis and a scalable hyper-ensemble solution
X Ding, L Zhao, L Akoglu
NeurIPS 2022, 2022
Graph Anomaly Detection with Unsupervised GNNs
L Zhao, S Sawlani, A Srinivasan, L Akoglu
ICDM 2022 short, 2022
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
Connecting graph convolutional networks and graph-regularized pca
L Zhao, L Akoglu
ICML 2020 Workshop, 2020
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
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
End-to-End Augmentation Hyperparameter Tuning for Self-Supervised Anomaly Detection
J Yoo, L Zhao, L Akoglu
arXiv preprint arXiv:2306.12033, 2023
Descriptive Kernel Convolution Network with Improved Random Walk Kernel
MC Lee*, L Zhao*, L Akoglu
2024 WWW, 2024
Improving and Unifying Discrete&Continuous-time Discrete Denoising Diffusion
L Zhao*, X Ding*, L Yu, L Akoglu
arXiv preprint arXiv:2402.03701, 2024
Pard: Permutation-Invariant Autoregressive Diffusion for Graph Generation
L Zhao, X Ding, L Akoglu
arXiv preprint arXiv:2402.03687, 2024
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