Zhao, Lingxiao

12 publications

JMLR 2025 Unified Discrete Diffusion for Categorical Data Lingxiao Zhao, Xueying Ding, Lijun Yu, Leman Akoglu

ICML 2024 On the Expressive Power of Spectral Invariant Graph Neural Networks Bohang Zhang, Lingxiao Zhao, Haggai Maron

NeurIPS 2024 Pard: Permutation-Invariant Autoregressive Diffusion for Graph Generation Lingxiao Zhao, Xueying Ding, Leman Akoglu

ECML-PKDD 2023 DSV: An Alignment Validation Loss for Self-Supervised Outlier Model Selection Jaemin Yoo, Yue Zhao, Lingxiao Zhao, Leman Akoglu

ICLR 2023 Sign and Basis Invariant Networks for Spectral Graph Representation Learning Derek Lim, Joshua David Robinson, Lingxiao Zhao, Tess Smidt, Suvrit Sra, Haggai Maron, Stefanie Jegelka

NeurIPS 2022 A Practical, Progressively-Expressive GNN Lingxiao Zhao, Neil Shah, Leman Akoglu

ICLR 2022 From Stars to Subgraphs: Uplifting Any GNN with Local Structure Awareness Lingxiao Zhao, Wei Jin, Leman Akoglu, Neil Shah

ICLR 2022 Graph Condensation for Graph Neural Networks Wei Jin, Lingxiao Zhao, Shichang Zhang, Yozen Liu, Jiliang Tang, Neil Shah

NeurIPS 2022 Hyperparameter Sensitivity in Deep Outlier Detection: Analysis and a Scalable Hyper-Ensemble Solution Xueying Ding, Lingxiao Zhao, Leman Akoglu

ICLRW 2022 Sign and Basis Invariant Networks for Spectral Graph Representation Learning Derek Lim, Joshua David Robinson, Lingxiao Zhao, Tess Smidt, Suvrit Sra, Haggai Maron, Stefanie Jegelka

NeurIPS 2020 Beyond Homophily in Graph Neural Networks: Current Limitations and Effective Designs Jiong Zhu, Yujun Yan, Lingxiao Zhao, Mark Heimann, Leman Akoglu, Danai Koutra

ICLR 2020 PairNorm: Tackling Oversmoothing in GNNs Lingxiao Zhao, Leman Akoglu