Jing Shao

Artificial Intelligence · with Chi · 2016

A researcher in the Science corpus: 1 paper; trusts 5 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 7 citations into it
• Representation & Self-Supervised Learning — 7 citations into it

Whom Jing Shao trusts overall

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

1. Marc'Aurelio Ranzato
2. Geoffrey E. Hinton

Papers from Jing Shao's perspective

Ordered by how strongly the researchers Jing Shao trusts endorse each paper. Same corpus, a different order for every researcher.

1. This PDF file includes: Materials and Methods
2. Learning Deep Architectures for AI
3. ImageNet classification with deep convolutional neural networks
4. Extracting and composing robust features with denoising autoencoders
5. A unified architecture for natural language processing: deep neural networks with multitask learning
6. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
7. Gradient-based learning applied to document recognition
8. Stacked Denoising Autoencoders: Learning Useful Representations in a Deep Network with a Local Denoising Criterion
9. Attention is All you Need (Neural Information Processing Systems)
10. Long Short-Term Memory

Their papers

• Deep learning architecture for air quality predictions (2016) — 317 citations