Che-Lun Hung

Artificial Intelligence · 2019

A researcher in the Science corpus: 1 paper; trusts 12 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 11 citations into it
• Computer Vision and Pattern Recognition — 11 citations into it
• Model Architectures — 10 citations into it

Whom Che-Lun Hung trusts overall

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

1. Geoffrey E. Hinton
2. Alex Krizhevsky
3. Yoshua Bengio
4. Kaiming He
5. Karen Simonyan
6. Ilya Sutskever
7. Yann LeCun
8. Xavier Glorot
9. Alex Graves
10. Kyunghyun Cho

Papers from Che-Lun Hung's perspective

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

Their papers

• NCNet: Deep Learning Network Models for Predicting Function of Non-coding DNA (2019) — 17 citations