2022

  1. Sign and Basis Invariant Networks for Spectral Graph Representation Learning Derek Lim*, Joshua Robinson*, Lingxiao Zhao, Tess Smidt, Suvrit Sra, Haggai Maron, and Stefanie Jegelka Under review 2022 [Abs] [PDF]
  2. From Stars to Subgraphs: Uplifting Any GNN with Local Structure Awareness Lingxiao Zhao, Wei Jin, Leman Akoglu, and Neil Shah ICLR 2022 [Abs] [PDF] [Slides] [Code]
  3. Graph Condensation for Graph Neural Networks Wei Jin, Lingxiao Zhao, Shichang Zhang, Yozen Liu, Jiliang Tang, and Neil Shah ICLR 2022 [Abs] [PDF] [Code]

2021

  1. Fast Attributed Graph Embedding via Density of States Saurabh Sawlani, Lingxiao Zhao, and Leman Akoglu IEEE ICDM 2021 2021 [Abs] [PDF] [Code]
  2. Connecting Graph Convolutional Network and Graph-Regularized PCA (Extended) Lingxiao Zhao, and Leman Akoglu Under review 2021 [Abs] [PDF] [Code]
  3. On Using Classification Datasets to Evaluate Graph Outlier Detection: Peculiar Observations and New Insights Lingxiao Zhao, and Leman Akoglu Big Data Journal, Special Issue on Evaluation and Experimental Design in Data Mining and Machine Learning, Aug. 2021 2021 [Abs] [PDF] [Code]

2020

  1. PairNorm: Tackling Oversmoothing in GNNs Lingxiao Zhao, and Leman Akoglu ICLR 2020, Addis Ababa, Ethiopia 2020 [Abs] [PDF] [Slides] [Code] [Video]
  2. Connecting Graph Convolutional Network and Graph-Regularized PCA Lingxiao Zhao, and Leman Akoglu ICML 2020 GRLP Workshop 2020 [Abs] [PDF]
  3. Generalizing Graph Neural Networks Beyond Homophily Jiong Zhu, Yujun Yan, Lingxiao Zhao, Mark Heimann, Leman Akoglu, and Danai Koutra arXiv preprint arXiv:2006.11468 2020 [Abs] [PDF]
  4. Graph Unrolling Networks: Interpretable Neural Networks for Graph Signal Denoising Siheng Chen, Yonina C Eldar, and Lingxiao Zhao arXiv preprint arXiv:2006.01301 2020 [Abs] [PDF]

2018

  1. A Quest for Structure: Jointly Learning the Graph Structure and Semi-Supervised Classification Xuan Wu*, Lingxiao Zhao*, and Leman Akoglu In Proceedings of the 27th ACM International Conference on Information and Knowledge Management 2018 [Abs] [PDF] [Slides] [Code]