Tianye Zhang

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 Tianye Zhang 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

Papers from Tianye Zhang's perspective

Ordered by how strongly the researchers Tianye Zhang 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. Learning Multiple Layers of Features from Tiny Images
5. Attention is All you Need (Neural Information Processing Systems)
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. Long Short-Term Memory
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