Yizhou Sun

Artificial Intelligence · Knowledge Discovery and Data Mining · 2009–2022

A researcher in the Science corpus: 21 papers; trusts 461 researchers and is trusted by 48 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 355 citations into it; #4,417 of 35,345 by trust here, #3,261 by citations
• Computer Vision and Pattern Recognition — 162 citations into it; #15,426 of 21,575 by trust here, #10,010 by citations
• Graph Learning — 126 citations into it; #317 of 693 by trust here, #266 by citations
• Representation & Self-Supervised Learning — 102 citations into it; #2,933 of 3,145 by trust here, #1,543 by citations
• Statistical and Nonlinear Physics — 95 citations into it; #1,029 of 10,127 by trust here, #617 by citations
• Information Systems — 90 citations into it; #1,254 of 8,771 by trust here, #413 by citations
• Natural Language Processing — 70 citations into it
• Molecular Biology — 50 citations into it

Whom Yizhou Sun trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Geoffrey E. Hinton
2. Diederik P. Kingma
3. Yoshua Bengio
4. Tomas Mikolov
5. Alex Krizhevsky
6. Ilya Sutskever
7. Yann LeCun
8. Kaiming He
9. Jiawei Han
10. L. Eon Bottou

Who trusts Yizhou Sun overall

1. Yuxiao Dong
2. Ting-Li Chen
3. Chuan Shi
4. Jiawei Han
5. Charu C. Aggarwal
6. Ziniu Hu
7. Nitesh V. Chawla
8. Xiang Ren
9. Yuhui Ding
10. Xiao Wang

Papers from Yizhou Sun's perspective

Ordered by how strongly the researchers Yizhou Sun trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Learning Multiple Layers of Features from Tiny Images
10. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)

Their papers

• On Sampling Strategies for Neural Network-based Collaborative Filtering (2017) — 258 citations
• Reveal: Retrieval-Augmented Visual-Language Pre-Training with Multi-Source Multimodal Knowledge Memory (2022) — 178 citations
• Graph Regularized Transductive Classification on Heterogeneous Information Networks (2010) — 261 citations
• Heterogeneous Graph Transformer (2020) — 1,684 citations
• Unsupervised Inductive Whole-Graph Embedding by Preserving Graph Proximity (2019) — 10 citations
• Unsupervised Inductive Graph-Level Representation Learning via Graph-Graph Proximity (2019) — 86 citations
• Relation-Guided Pre-Training for Open-Domain Question Answering (2021) — 6 citations
• PathSim (2011) — 1,600 citations
• Layer-Dependent Importance Sampling for Training Deep and Large Graph Convolutional Networks (2019) — 339 citations
• SimGNN: A Neural Network Approach to Fast Graph Similarity Computation (2018) — 409 citations
• Personalized entity recommendation: a heterogeneous information network approach (2014) — 774 citations
• Clinical Temporal Relation Extraction with Probabilistic Soft Logic Regularization and Global Inference (2020) — 55 citations
• GPT-GNN: Generative Pre-Training of Graph Neural Networks (2020) — 687 citations
• Joint Text Embedding for Personalized Content-based Recommendation (2017) — 31 citations
• Entity Embedding-Based Anomaly Detection for Heterogeneous Categorical Events (2016) — 91 citations
• Task-Guided and Path-Augmented Heterogeneous Network Embedding for Author Identification (2016) — 229 citations
• Mining heterogeneous information networks: a structural analysis approach (2013) — 648 citations
• Mining Heterogeneous Information Networks: Principles and Methodologies (2012) — 553 citations
• Co-author Relationship Prediction in Heterogeneous Bibliographic Networks (2011) — 462 citations
• Ranking-based clustering of heterogeneous information networks with star network schema (2009) — 553 citations