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Edwin R. Hancock

13 papers at tracked venues · 8 at CORE A* · active 2024–2026

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Venues

IJCAI ×5AAAI ×2ICDE ×2ICML ×2NeurIPS ×2

Frequent coauthors

Lu Bai
×13
Lixin Cui
×13
Ming Li
×13
Yue Wang
×10
Hangyuan Du
×8
Ziyu Lyu
×4
Feifei Qian
×3
Xinya Qin
×3
Zhuo Xu
×2
Philip S. Yu
×2
Zhehan Zhao
×2
Peng Ren
×1

Papers

  1. SSHPool: The Separated Subgraph-based Hierarchical Pooling
    AAAI 2026 ·
    Zhuo Xu
    ,
    Lu Bai
    ,
    Lixin Cui
    ,
    Ming Li
    ,
    Hangyuan Du
    ,
    Ziyu Lyu
    ,
    Yue Wang
    , Edwin R. Hancock
  2. AEGK: Aligned Entropic Graph Kernels Through Continuous-Time Quantum Walks: (Extended Abstract)
    ICDE 2025 ·
    Lu Bai
    ,
    Lixin Cui
    ,
    Ming Li
    ,
    Peng Ren
    ,
    Yue Wang
    ,
    Lichi Zhang
    ,
    Philip S. Yu
    , Edwin R. Hancock
  3. AKBR: Learning Adaptive Kernel-based Representations for Graph Classification
    IJCAI 2025 ·
    Lu Bai
    ,
    Feifei Qian
    ,
    Lixin Cui
    ,
    Ming Li
    ,
    Hangyuan Du
    ,
    Yue Wang
    , Edwin R. Hancock
  4. An End-to-End Simple Clustering Hierarchical Pooling Operation for Graph Learning Based on Top-K Node Selection
    IJCAI 2025 ·
    Zhehan Zhao
    ,
    Lu Bai
    ,
    Ming Li
    ,
    Lixin Cui
    ,
    Hangyuan Du
    ,
    Yue Wang
    , Edwin R. Hancock
  5. DHAKR: Learning Deep Hierarchical Attention-Based Kernelized Representations for Graph Classification
    AAAI 2025 ·
    Feifei Qian
    ,
    Lu Bai
    ,
    Lixin Cui
    ,
    Ming Li
    ,
    Ziyu Lyu
    ,
    Hangyuan Du
    , Edwin R. Hancock
  6. DHTAGK: Deep Hierarchical Transitive-Aligned Graph Kernels for Graph Classification
    IJCAI 2025 ·
    Xinya Qin
    ,
    Lu Bai
    ,
    Lixin Cui
    ,
    Ming Li
    ,
    Ziyu Lyu
    ,
    Hangyuan Du
    , Edwin R. Hancock
  7. ENAHPool: The Edge-Node Attention-based Hierarchical Pooling for Graph Neural Networks
    ICML 2025 ·
    Zhehan Zhao
    ,
    Lu Bai
    ,
    Lixin Cui
    ,
    Ming Li
    ,
    Ziyu Lyu
    ,
    Lixiang Xu
    ,
    Yue Wang
    , Edwin R. Hancock
  8. Exploring the Over-smoothing Problem of Graph Neural Networks for Graph Classification: An Entropy-based Viewpoint
    IJCAI 2025 ·
    Feifei Qian
    ,
    Lu Bai
    ,
    Lixin Cui
    ,
    Ming Li
    ,
    Hangyuan Du
    ,
    Yue Wang
    , Edwin R. Hancock
  9. HA-SCN: Learning Hierarchical Aligned Subtree Convolutional Networks for Graph Classification
    IJCAI 2025 ·
    Xinya Qin
    ,
    Lu Bai
    ,
    Lixin Cui
    ,
    Ming Li
    ,
    Hangyuan Du
    ,
    Yue Wang
    , Edwin R. Hancock
  10. HAQJSK: Hierarchical-Aligned Quantum Jensen-Shannon Kernels for Graph Classification (Extended Abstract)
    ICDE 2025 ·
    Lu Bai
    ,
    Lixin Cui
    ,
    Yue Wang
    ,
    Ming Li
    ,
    Jing Li
    ,
    Philip S. Yu
    , Edwin R. Hancock
  11. MultiNet: Adaptive Multi-Viewed Subgraph Convolutional Networks for Graph Classification
    NeurIPS 2025 ·
    Xinya Qin
    ,
    Lu Bai
    ,
    Lixin Cui
    ,
    Ming Li
    ,
    Hangyuan Du
    , Edwin R. Hancock
  12. HC-GAE: The Hierarchical Cluster-based Graph Auto-Encoder for Graph Representation Learning
    NeurIPS 2024 ·
    Lu Bai
    ,
    Zhuo Xu
    ,
    Lixin Cui
    ,
    Ming Li
    ,
    Yue Wang
    , Edwin R. Hancock
  13. QBMK: Quantum-based Matching Kernels for Un-attributed Graphs
    ICML 2024 ·
    Lu Bai
    ,
    Lixin Cui
    ,
    Ming Li
    ,
    Yue Wang
    , Edwin R. Hancock