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Computer Science

D-Index
63
Citations
22686
World Ranking
2697
National Ranking
370

Research.com Recognitions

  • 2020 - ACM Distinguished Member

Overview

Peng Cui is affiliated with Tsinghua University in China and focuses on research within the field of computer science.

Their work spans several specialized subfields including artificial intelligence, computer vision and pattern recognition, information systems, management science and operations research, and statistics and probability.

Key research topics covered by Peng Cui include advanced graph neural networks, domain adaptation and few-shot learning, recommender systems and techniques, topic modeling, complex network analysis techniques, Gaussian processes and Bayesian inference, as well as machine learning and data classification.

Frequent publication venues for Peng Cui's work are:

  • arXiv (Cornell University)
  • IEEE Transactions on Knowledge and Data Engineering
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
  • IEEE Transactions on Pattern Analysis and Machine Intelligence

Peng Cui has collaborated multiple times with several coauthors, including:

  • Zheyan Shen
  • Wenwu Zhu
  • Renzhe Xu
  • Jiashuo Liu
  • Ziwei Zhang

Notable recent publications by Peng Cui include:

  • "Stable learning establishes some common ground between causal inference and machine learning," 2022, Nature Machine Intelligence
  • "Deep Learning on Graphs: A Survey," 2020, IEEE Transactions on Knowledge and Data Engineering
  • "Towards Out-Of-Distribution Generalization: A Survey," 2021, arXiv (Cornell University)
  • "Graph Neural Networks: Foundation, Frontiers and Applications," 2022, Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
  • "Towards Non-I.I.D. image classification: A dataset and baselines," 2020, Pattern Recognition

Peng Cui received the ACM Distinguished Member award in 2020.

Best Publications

  • Structural Deep Network Embedding

    Daixin Wang;Peng Cui;Wenwu Zhu

  • Heterogeneous Graph Attention Network

    Xiao Wang;Houye Ji;Chuan Shi;Bai Wang

  • Deep Learning on Graphs: A Survey

    Ziwei Zhang;Peng Cui;Wenwu Zhu

  • Asymmetric Transitivity Preserving Graph Embedding

    Mingdong Ou;Peng Cui;Jian Pei;Ziwei Zhang

  • A Survey on Network Embedding

    Peng Cui;Xiao Wang;Jian Pei;Wenwu Zhu

  • Community preserving network embedding

    Xiao Wang;Peng Cui;Jing Wang;Jian Pei

  • Structural Deep Clustering Network

    Deyu Bo;Xiao Wang;Chuan Shi;Meiqi Zhu

  • AM-GCN: Adaptive Multi-channel Graph Convolutional Networks

    Xiao Wang;Meiqi Zhu;Deyu Bo;Peng Cui

  • Robust Graph Convolutional Networks Against Adversarial Attacks

    Dingyuan Zhu;Ziwei Zhang;Peng Cui;Wenwu Zhu

  • Social contextual recommendation

    Meng Jiang;Peng Cui;Rui Liu;Qiang Yang

  • A Semi-supervised Graph Attentive Network for Financial Fraud Detection

    Daixin Wang;Jianbin Lin;Peng Cui;Quanhui Jia

  • A Semi-Supervised Graph Attentive Network for Financial Fraud Detection

    Daixin Wang;Yuan Qi;Jianbin Lin;Peng Cui

  • Deep Stable Learning for Out-Of-Distribution Generalization

    Xingxuan Zhang;Peng Cui;Renzhe Xu;Linjun Zhou

  • Towards Out-Of-Distribution Generalization: A Survey

    Zheyan Shen;Jiashuo Liu;Yue He;Xingxuan Zhang

  • Disentangled Self-Supervision in Sequential Recommenders

    Jianxin Ma;Chang Zhou;Hongxia Yang;Peng Cui

  • Scalable Recommendation with Social Contextual Information

    Meng Jiang;Peng Cui;Fei Wang;Wenwu Zhu

  • Arbitrary-Order Proximity Preserved Network Embedding

    Ziwei Zhang;Peng Cui;Xiao Wang;Jian Pei

  • CatchSync: catching synchronized behavior in large directed graphs

    Meng Jiang;Peng Cui;Alex Beutel;Christos Faloutsos

  • Learning Disentangled Representations for Recommendation

    Jianxin Ma;Chang Zhou;Peng Cui;Hongxia Yang

  • Who should share what?: item-level social influence prediction for users and posts ranking

    Peng Cui;Fei Wang;Shaowei Liu;Mingdong Ou

  • Disentangled Graph Convolutional Networks

    Jianxin Ma;Peng Cui;Kun Kuang;Xin Wang

  • Heterogeneous Graph Attention Network.

    Xiao Wang;Houye Ji;Chuan Shi;Bai Wang

Frequent Co-Authors

Wenwu Zhu
Wenwu Zhu Tsinghua University
Shiqiang Yang
Shiqiang Yang Tsinghua University
Meicheng Li
Meicheng Li North China Electric Power University
Meng Jiang
Meng Jiang University of Notre Dame
Christos Faloutsos
Christos Faloutsos Carnegie Mellon University
Jian Pei
Jian Pei Duke University
Pooi See Lee
Pooi See Lee Nanyang Technological University
Gang Cheng
Gang Cheng Henan University
Zuliang Du
Zuliang Du Henan University
Chuan Shi
Chuan Shi Beijing University of Posts and Telecommunications

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