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Hangyuan Du

10 papers · 2025–2026 · 2 venues · across top CS/AI venues

Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.

Achievements

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+1 more ↓ 🌍 Conference Polyglot · Bronze 🗺️ Taxonomy Completionist (12) ⭐ Rising Star (10) 🔬 Deep Specialist (10) 💎 Century Club · Bronze
⚡ Prolific Year · Productive

Venues

AAAI (5) IJCAI (5)

Top co-authors

Lixin Cui (9) Lu Bai (8) Ming Li (7) Edwin Hancock (6) Yue Wang (5) Feifei Qian (3) Ziyu Lyu (3) Xinya Qin (2) Liang Bai (2) Xian Yang (1)

Research topics

Deep Learning (10) Architectures (10) Machine Learning (8) Core Methods (7) Artificial Intelligence (2) Core AI (2) Application Areas (1) Optimization & Theory · Machine Learning (1) Optimization & Theory · Deep Learning (1) Techniques (1)

Keywords

graph neural network (9) graph classification (7) attention mechanism (3) graph kernel (2) out-of-distribution generalization (2) representation learning (2) mutual information (1) weisfeiler-lehman test (1) end-to-end learning (1) codebook learning (1) causal intervention (1) hierarchical feature (1) graph autoencoder (1) counterfactual regularization (1) jensen-shannon divergence (1) hierarchical pooling (1) convolutional filter (1) graph pooling (1) entropy-based analysis (1) node feature discretization (1)

Papers

CauVQ: Causal Vector Quantization for Graph OOD Generalization AAAI 2026 GCIB: Causal Intervention Guided Graph Information Bottleneck Framework AAAI 2026 LGAN: An Efficient High-Order Graph Neural Network via the Line Graph Aggregation AAAI 2026 SSHPool: The Separated Subgraph-based Hierarchical Pooling AAAI 2026 AKBR: Learning Adaptive Kernel-based Representations for Graph Classification IJCAI 2025 An End-to-End Simple Clustering Hierarchical Pooling Operation for Graph Learning Based on Top-K Node Selection IJCAI 2025 DHAKR: Learning Deep Hierarchical Attention-Based Kernelized Representations for Graph Classification AAAI 2025 DHTAGK: Deep Hierarchical Transitive-Aligned Graph Kernels for Graph Classification IJCAI 2025 Exploring the Over-smoothing Problem of Graph Neural Networks for Graph Classification: An Entropy-based Viewpoint IJCAI 2025 HA-SCN: Learning Hierarchical Aligned Subtree Convolutional Networks for Graph Classification IJCAI 2025