Chun-Kit Yeung

Artificial Intelligence · 2018

A researcher in the Science corpus: 1 paper; trusts 8 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 6 citations into it; #24,734 of 35,345 by trust here, #32,362 by citations
• Computer Science Applications — 5 citations into it; #1,050 of 1,855 by trust here, #1,676 by citations

Whom Chun-Kit Yeung trusts overall

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

1. Zachary Chase Lipton
2. Lutz Prechelt
3. Hao Cen
4. Jiani Zhang
5. C. Piech
6. K. Koedinger
7. Xingjian Shi
8. Z. Pardos
9. Brian W. Junker
10. Michael V. Yudelson

Who trusts Chun-Kit Yeung overall

1. Aritra Ghosh
2. Neil Heffernan III
3. Andrew S. Lan

Papers from Chun-Kit Yeung's perspective

Ordered by how strongly the researchers Chun-Kit Yeung trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Attention is All you Need (Neural Information Processing Systems)
5. Gradient-based learning applied to document recognition
6. Long Short-Term Memory
7. ImageNet: A large-scale hierarchical image database
8. ImageNet Large Scale Visual Recognition Challenge
9. Going deeper with convolutions
10. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)

Their papers

• Addressing two problems in deep knowledge tracing via prediction-consistent regularization (2018) — 341 citations