Guodong Long

Artificial Intelligence · 2016–2022

A researcher in the Science corpus: 20 papers; trusts 821 researchers and is trusted by 54 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 620 citations into it; #4,577 of 35,345 by trust here, #1,991 by citations
• Computer Vision and Pattern Recognition — 240 citations into it; #12,645 of 21,575 by trust here, #3,089 by citations
• Natural Language Processing — 203 citations into it; #4,686 of 5,688 by trust here, #2,011 by citations
• Graph Learning — 152 citations into it; #519 of 693 by trust here, #94 by citations
• Representation & Self-Supervised Learning — 123 citations into it
• Statistical and Nonlinear Physics — 103 citations into it; #3,908 of 10,127 by trust here, #2,316 by citations
• Model Architectures — 80 citations into it; #1,077 of 2,278 by trust here, #652 by citations
• Federated & Distributed Learning — 60 citations into it

Whom Guodong Long trusts overall

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

1. Geoffrey E. Hinton
2. Yoshua Bengio
3. Alex Krizhevsky
4. Diederik P. Kingma
5. Kaiming He
6. Ilya Sutskever
7. Yann LeCun
8. Richard Socher
9. Radford M. Neal
10. Ruslan Salakhutdinov

Who trusts Guodong Long overall

1. Yue Tan
2. Shirui Pan
3. Tianyi Zhou
4. Zezhi Shao
5. Mang Ye
6. Jing Jiang
7. Michael Hahn
8. Wenke Huang
9. Yixin Liu
10. Tao Shen

Papers from Guodong Long's perspective

Ordered by how strongly the researchers Guodong Long 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

• A Comprehensive Survey on Graph Neural Networks (2019) — 11,551 citations
• Reinforced Self-Attention Network: a Hybrid of Hard and Soft Attention for Sequence Modeling (2018) — 148 citations
• A Universal Representation Transformer Layer for Few-Shot Image Classification (2020) — 144 citations
• DiSAN: Directional Self-Attention Network for RNN/CNN-free Language Understanding (2017) — 787 citations
• Bi-Directional Block Self-Attention for Fast and Memory-Efficient Sequence Modeling (2018) — 153 citations
• Exploiting Structured Knowledge in Text via Graph-Guided Representation Learning (2020) — 72 citations
• Connecting the Dots: Multivariate Time Series Forecasting with Graph Neural Networks (2020) — 2,163 citations
• MGAE: Marginalized Graph Autoencoder for Graph Clustering (2017) — 521 citations
• Adversarially Regularized Graph Autoencoder (2018) — 489 citations
• Suicidal Ideation Detection: A Review of Machine Learning Methods and Applications (2019) — 228 citations
• Federated Learning from Pre-Trained Models: A Contrastive Learning Approach (2022) — 296 citations
• FedProto: Federated Prototype Learning across Heterogeneous Clients (2021) — 940 citations
• Federated Learning for Open Banking (2021) — 370 citations
• Multi-center federated learning: clients clustering for better personalization (2020) — 379 citations
• Structure-Augmented Text Representation Learning for Efficient Knowledge Graph Completion (2020) — 334 citations
• Attributed Graph Clustering: A Deep Attentional Embedding Approach (2019) — 645 citations
• Learning Graph Embedding With Adversarial Training Methods (2019) — 347 citations
• Graph WaveNet for Deep Spatial-Temporal Graph Modeling (2019) — 3,288 citations
• Fast Directional Self-Attention Mechanism (2018) — 5 citations
• Inferring Latent Network from Cascade Data for Dynamic Social Recommendation (2016) — 13 citations