Gan Sun

Artificial Intelligence · 2017–2022

A researcher in the Science corpus: 8 papers; trusts 430 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 139 citations into it; #19,579 of 35,345 by trust here, #13,544 by citations
• Computer Vision and Pattern Recognition — 108 citations into it; #12,271 of 21,575 by trust here, #11,498 by citations
• Representation & Self-Supervised Learning — 41 citations into it
• Meta & Continual Learning — 25 citations into it
• Optimization & Training — 19 citations into it
• Computational Mechanics — 17 citations into it
• Safety, Robustness & Interpretability — 13 citations into it
• Evaluation & Benchmarks — 11 citations into it

Whom Gan Sun trusts overall

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

1. Geoffrey E. Hinton
2. Kaiming He
3. Alex Krizhevsky
4. Paul Ruvolo
5. Karen Simonyan
6. Yoshua Bengio
7. Yann LeCun
8. Diederik P. Kingma
9. Ross B. Girshick
10. Andrew Zisserman

Who trusts Gan Sun overall

1. Xinting Hu
2. Yahao Liu
3. Tong Chu
4. Zhen Fang
5. Lixu Wang
6. Jiahua Dong
7. Priyanka Mary Mammen
8. Yi Jiang
9. Yue Wu

Papers from Gan Sun's perspective

Ordered by how strongly the researchers Gan 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. Gradient-based learning applied to document recognition
5. ImageNet: A large-scale hierarchical image database
6. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
7. Long Short-Term Memory
8. Attention is All you Need (Neural Information Processing Systems)
9. Learning Multiple Layers of Features from Tiny Images
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Active Lifelong Learning With "Watchdog" (2018) — 35 citations
• Lifelong Metric Learning (2017) — 28 citations
• Data Poisoning Attacks on Federated Machine Learning (2020) — 293 citations
• Federated Class-Incremental Learning (2022) — 299 citations
• Where and How to Transfer: Knowledge Aggregation-Induced Transferability Perception for Unsupervised Domain Adaptation (2021) — 153 citations
• L3DOC: Lifelong 3D Object Classification (2021) — 48 citations
• What Can Be Transferred: Unsupervised Domain Adaptation for Endoscopic Lesions Segmentation (2020) — 149 citations
• I3DOL: Incremental 3D Object Learning without Catastrophic Forgetting (2020) — 39 citations