Selected Publications

Citation Statistics

Asterisk marks (*) indicate authors having contributed (almost) equally.

Conference Papers

  • Code Recommendation for Open Source Software Developers
    • Yiqiao Jin,
    • Yunsheng Bai,
    • Yanqiao Zhu,
    • Yizhou Sun,
    • Wei Wang

    WWW 2023

  • A Survey on Deep Graph Generation: Methods and Applications
    • Yanqiao Zhu*,
    • Yuanqi Du*,
    • Yinkai Wang*,
    • Yichen Xu,
    • Jieyu Zhang,
    • Qiang Liu,
    • Shu Wu

    LoG 2022

  • Deep Contrastive Multiview Network Embedding
    • Mengqi Zhang*,
    • Yanqiao Zhu*,
    • Qiang Liu,
    • Shu Wu,
    • Liang Wang

    CIKM 2022

  • Interpretable Graph Neural Networks for Connectome-Based Brain Disorder Analysis
    • Hejie Cui,
    • Wei Dai,
    • Yanqiao Zhu,
    • Xiaoxiao Li,
    • Lifang He,
    • Carl Yang

    MICCAI 2022 (Oral)

  • Data-Efficient Brain Connectome Analysis via Multi-Task Meta-Learning
    • Yi Yang*,
    • Yanqiao Zhu*,
    • Hejie Cui,
    • Xuan Kan,
    • Lifang He,
    • Ying Guo,
    • Carl Yang

    KDD 2022 (Health Day)

  • Structure-Enhanced Heterogeneous Graph Contrastive Learning
    • Yanqiao Zhu*,
    • Yichen Xu*,
    • Hejie Cui,
    • Carl Yang,
    • Qiang Liu,
    • Shu Wu

    SDM 2022

  • An Empirical Study of Graph Contrastive Learning
    • Yanqiao Zhu,
    • Yichen Xu,
    • Qiang Liu,
    • Shu Wu

    NeurIPS 2021 (Datasets and Benchmarks)

  • Disentangled Self-Attentive Neural Networks for Click-Through Rate Prediction
    • Yichen Xu*,
    • Yanqiao Zhu*,
    • Feng Yu,
    • Qiang Liu,
    • Shu Wu

    CIKM 2021

  • Mining Latent Structures for Multimedia Recommendation
    • Jinghao Zhang*,
    • Yanqiao Zhu*,
    • Qiang Liu,
    • Shu Wu,
    • Shuhui Wang,
    • Liang Wang

    ACMMM 2021 (Oral)

  • Graph Contrastive Learning with Adaptive Augmentation
    • Yanqiao Zhu*,
    • Yichen Xu*,
    • Feng Yu,
    • Qiang Liu,
    • Shu Wu,
    • Liang Wang

    WWW 2021

  • TAGNN: Target Attentive Graph Neural Networks for Session-based Recommendation
    • Feng Yu*,
    • Yanqiao Zhu*,
    • Qiang Liu,
    • Shu Wu,
    • Liang Wang,
    • Tieniu Tan

    SIGIR 2020

  • Session-based Recommendation with Graph Neural Networks
    • Shu Wu,
    • Yuyuan Tang,
    • Yanqiao Zhu,
    • Liang Wang,
    • Xing Xie,
    • Tieniu Tan

    AAAI 2019 (Oral)

Journal Papers

  • Latent Structure Mining with Contrastive Modality Fusion for Multimedia Recommendation
    • Jinghao Zhang,
    • Yanqiao Zhu,
    • Qiang Liu,
    • Mengqi Zhang,
    • Shu Wu,
    • Liang Wang

    IEEE Trans. Knowl. Data Eng.

  • BrainGB: A Benchmark for Brain Network Analysis with Graph Neural Networks
    • Hejie Cui,
    • Wei Dai,
    • Yanqiao Zhu,
    • Xuan Kan,
    • Antonio Aodong Chen Gu,
    • Joshua Lukemire,
    • Liang Zhan,
    • Lifang He,
    • Ying Guo,
    • Carl Yang

    IEEE Trans. Med. Imaging

  • Active Learning for Wireless IoT Intrusion Detection
    • Kai Yang,
    • Jie Ren,
    • Yanqiao Zhu,
    • Weiyi Zhang

    IEEE Wirel. Commun. 25 (6)

Workshop Papers

  • Deep Graph Contrastive Representation Learning
    • Yanqiao Zhu*,
    • Yichen Xu*,
    • Feng Yu,
    • Qiang Liu,
    • Shu Wu,
    • Liang Wang

    GRL+@ICML 2020

Preprints

  • A Survey on Pretrained Language Models for Neural Code Intelligence
    • Yichen Xu,
    • Yanqiao Zhu
  • A Systematic Survey of Molecular Pre-trained Models
    • Jun Xia,
    • Yanqiao Zhu,
    • Yuanqi Du,
    • Yue Liu,
    • Stan Z. Li
  • A Survey on Graph Structure Learning: Progress and Promise
    • Yanqiao Zhu,
    • Shichang Zhang,
    • Weizhi Xu,
    • Jinghao Zhang,
    • Yuanqi Du,
    • Jieyu Zhang,
    • Qiang Liu,
    • Shu Wu,
    • Yizhou Sun,
    • Wei Wang
  • Unsupervised Graph Representation Learning with Cluster-Aware Self-Training and Refining
    • Yanqiao Zhu*,
    • Yichen Xu*,
    • Feng Yu,
    • Qiang Liu,
    • Shu Wu