Yu-Wei Kao

Artificial Intelligence · 2019

A researcher in the Science corpus: 1 paper; trusts 35 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 22 citations into it
• Optimization & Training — 18 citations into it
• Computer Vision and Pattern Recognition — 15 citations into it
• Model Architectures — 13 citations into it
• Representation & Self-Supervised Learning — 5 citations into it

Whom Yu-Wei Kao trusts overall

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

1. Yoshua Bengio
2. Geoffrey E. Hinton
3. Yann LeCun
4. L. V. D. van der Maaten
5. Alex Krizhevsky
6. Sepp Hochreiter
7. Kaiming He
8. L. Eon Bottou
9. Diederik P. Kingma
10. Ilya Sutskever

Papers from Yu-Wei Kao's perspective

Ordered by how strongly the researchers Yu-Wei Kao 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. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
8. Learning Multiple Layers of Features from Tiny Images
9. ImageNet: A large-scale hierarchical image database
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Associated Learning: Decomposing End-to-End Backpropagation Based on Autoencoders and Target Propagation (2019) — 8 citations