Fan-Keng Sun

Artificial Intelligence · 2018–2020

A researcher in the Science corpus: 4 papers; trusts 131 researchers and is trusted by 18 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 71 citations into it; #11,418 of 35,345 by trust here, #12,083 by citations
• Computer Vision and Pattern Recognition — 32 citations into it; #8,899 of 21,575 by trust here, #8,952 by citations
• Natural Language Processing — 25 citations into it
• Model Architectures — 20 citations into it
• Meta & Continual Learning — 16 citations into it; #374 of 1,041 by trust here, #369 by citations
• Representation & Self-Supervised Learning — 15 citations into it
• Signal Processing — 8 citations into it; #5,948 of 7,572 by trust here, #5,570 by citations
• Large Language Models — 7 citations into it; #218 of 799 by trust here, #503 by citations

Whom Fan-Keng Sun trusts overall

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

1. Alec Radford
2. Yoshua Bengio
3. Geoffrey E. Hinton
4. Ilya Sutskever
5. Alex Krizhevsky
6. Yann LeCun
7. Diederik P. Kingma
8. Kaiming He
9. Sepp Hochreiter
10. Alex Graves

Who trusts Fan-Keng Sun overall

1. Yannis Papanikolaou
2. Zixuan Ke
3. Yanzhe Zhang
4. Nithin Holla
5. Eyal Ben-David
6. Andrea Pierleoni
7. Angeliki Lazaridou
8. Aman Hussain
9. Yung-Sung Chuang
10. Zirui Wang

Papers from Fan-Keng Sun's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
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. ImageNet Large Scale Visual Recognition Challenge
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• LAMOL: LAnguage MOdeling for Lifelong Language Learning (2019) — 253 citations
• Temporal pattern attention for multivariate time series forecasting (2018) — 907 citations
• Conditioned Natural Language Generation using only Unconditioned Language Model: An Exploration (2020) — 18 citations
• LAMAL: LAnguage Modeling Is All You Need for Lifelong Language Learning (2019) — 39 citations