Wei Chen

Computer Vision and Pattern Recognition · with Chen · 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 Wei Chen trusts

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

1. Carl Doersch (in Computer Vision and Pattern Recognition)
2. Dong-Hyun Lee (in Representation & Self-Supervised Learning)
3. Emilien Dupont (in Computer Vision and Pattern Recognition)
4. Geoffrey E. Hinton (in Artificial Intelligence)

Papers from Wei Chen's perspective

Ordered by how strongly the researchers Wei Chen 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. mixup: Beyond Empirical Risk Minimization
8. Long Short-Term Memory
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. beta-VAE: Learning Basic Visual Concepts with a Constrained Variational Framework

Their papers

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