Hong Kong

Artificial Intelligence · 2021

A researcher in the Science corpus: 1 paper; trusts 9 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 35 citations into it
• Computer Vision and Pattern Recognition — 23 citations into it

Whom Hong Kong trusts overall

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

1. Geoffrey E. Hinton

Papers from Hong Kong's perspective

Ordered by how strongly the researchers Hong 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. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
3. ImageNet classification with deep convolutional neural networks
4. Dropout: a simple way to prevent neural networks from overfitting
5. Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
6. Gradient-based learning applied to document recognition
7. Matching Networks for One Shot Learning
8. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
9. Long Short-Term Memory
10. Attention is All you Need (Neural Information Processing Systems)

Their papers

• Mutual CRF-GNN for Few-shot Learning (2021) — 60 citations