Kezhi Kong

Computer Vision and Pattern Recognition · 2020

A researcher in the Science corpus: 1 paper; trusts 4 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 21 citations into it
• Artificial Intelligence — 19 citations into it
• Representation & Self-Supervised Learning — 17 citations into it
• Generative Models — 9 citations into it
• Optimization & Training — 5 citations into it

Whom Kezhi Kong trusts overall

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

1. Geoffrey E. Hinton
2. Carl Doersch
3. David Berthelot
4. Dong-Hyun Lee
5. Diederik P. Kingma
6. Emilien Dupont
7. Yoshua Bengio
8. Alex Krizhevsky
9. Kaiming He
10. Yann LeCun

Papers from Kezhi Kong's perspective

Ordered by how strongly the researchers Kezhi Kong 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. Gradient-based learning applied to document recognition
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Attention is All you Need (Neural Information Processing Systems)
6. Long Short-Term Memory
7. Learning Multiple Layers of Features from Tiny Images
8. ImageNet: A large-scale hierarchical image database
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. Going deeper with convolutions

Their papers

• SHOT-VAE: Semi-supervised Deep Generative Models With Label-aware ELBO Approximations (2020) — 29 citations