Hanchen Wang
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    • 🎉 One paper accepted by NeurIPS 2025
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    • Towards Unsupervised Training of Matching-based Graph Edit Distance Solver via Preference-aware GAN
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    • AIGC for Graphs: Current Techniques and Future Trends
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    • Temporal Insights for Group-Based Fraud Detection on e-Commerce Platforms
    • Deep Learning Approaches for Similarity Computation: A Survey
    • Bipartite Graph Analytics: Current Techniques and Future Trends
    • Simple and Deep Graph Attention Networks
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    • TIformer: A Transformer-Based Framework for Time-Series Forecasting with Missing Data
    • FPGN: follower prediction framework for infectious disease prevention
    • Group-based Fraud Detection Network on e-Commerce Platforms
    • Denoising Variational Graph of Graphs Auto-Encoder for Predicting Structured Entity Interactions
    • Neural Similarity Search on Supergraph Containment
    • TMN: Trajectory Matching Networks for Learning Similarity Computation
    • Neural Subgraph Counting with Wasserstein Estimator
    • Reinforcement Learning Based Query Vertex Ordering Model for Subgraph Matching
    • Polarity-based Graph Neural Network for Sign Prediction in Signed Bipartite Graphs
    • Bipartite Graph Capsule Network
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    • T3S: Effective Representation Learning for Trajectory Similarity Computation
    • EI-LSH: An early-termination driven I/O efficient incremental c-approximate nearest neighbor search
    • GoGNN: Graph of Graphs Neural Network for Predicting Structured Entity Interactions
    • I/O Efficient Algorithm for c-Approximate Furthest Neighbor Search in High-Dimensional Space
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    • I-LSH: I/O Efficient c-Approximate Nearest Neighbor Search in High-Dimensional Space
  • Students
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    • Jianke Yu
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    • Yunyi Zhu
    • Han Chen
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    • Runze Li
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    • Xingyu Tan
    • Mengting Pan
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Yifan Zhu

· 0 min read
Last updated on Jul 15, 2025
Current MPhil
Hanchen Wang
Authors
Hanchen Wang
ARC DECRA Fellow, Lecturer
← Xinyi Li Jan 1, 0001
Yunyi Zhu Jan 1, 0001 →

© 2025 Hanchen Wang. This work is licensed under CC BY NC ND 4.0

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