InParformer: Evolutionary Decomposition Transformers with Interactive Parallel Attention for Long-Term Time Series Forecasting. - Haizhou Cao; Zhenhao Huang 001; Tiechui Yao; Jue Wang 013; Hui He; Yangang Wang (AAAI, 2023)

DeepRicci: Self-supervised Graph Structure-Feature Co-Refinement for Alleviating Over-squashing. - Li Sun 008; Zhenhao Huang 001; Hua Wu; Junda Ye; Hao Peng 001; Zhengtao Yu 001; Philip S. Yu (ICDM, 2023)

Motif-Aware Riemannian Graph Neural Network with Generative-Contrastive Learning. - Li Sun 008; Zhenhao Huang 001; Zixi Wang; Feiyang Wang; Hao Peng 001; Philip S. Yu (AAAI, 2024)

LSEnet: Lorentz Structural Entropy Neural Network for Deep Graph Clustering. - Li Sun 008; Zhenhao Huang 001; Hao Peng 001; Yujie Wang; Chunyang Liu; Philip S. Yu (ICML, 2024)

Spiking Graph Neural Network on Riemannian Manifolds. - Li Sun 008; Zhenhao Huang 001; Qiqi Wan; Hao Peng 001; Philip S. Yu (NeurIPS, 2024)

RicciNet: Deep Clustering via A Riemannian Generative Model. - Li Sun 008; Jingbin Hu; Suyang Zhou; Zhenhao Huang 001; Junda Ye; Hao Peng 001; Zhengtao Yu 001; Philip S. Yu (WWW, 2024)

RiemannGFM: Learning a Graph Foundation Model from Riemannian Geometry. - Li Sun 008; Zhenhao Huang 001; Suyang Zhou; Qiqi Wan; Hao Peng 001; Philip S. Yu (WWW, 2025)

IsoSEL: Isometric Structural Entropy Learning for Deep Graph Clustering in Hyperbolic Space. - Li Sun 008; Zhenhao Huang 001; Yujie Wang; Hongbo Lv; Chunyang Liu; Hao Peng 001; Philip S. Yu (CoRR, 2025)