Nanbo Li

Computer Vision and Pattern Recognition · 2021

A researcher in the Science corpus: 1 paper; trusts 16 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 16 citations into it; #17,129 of 21,575 by trust here, #20,756 by citations
• Artificial Intelligence — 10 citations into it; #28,025 of 35,345 by trust here, #33,294 by citations
• Representation & Self-Supervised Learning — 10 citations into it
• Generative Models — 9 citations into it

Whom Nanbo Li trusts overall

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

1. Christopher K. I. Williams
2. Klaus Greff
3. Diederik P. Kingma
4. Geoffrey E. Hinton
5. Cian Eastwood
6. J. Urgen Schmidhuber
7. Joseph Marino
8. Yoshua Bengio
9. Christopher P. Burgess
10. Alex Krizhevsky

Who trusts Nanbo Li overall

1. Matthew James Vowels
2. Necati Cihan Camgöz
3. Michael Niemeyer

Papers from Nanbo Li's perspective

Ordered by how strongly the researchers Nanbo Li 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Gradient-based learning applied to document recognition
5. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. Auto-Encoding Variational Bayes (International Conference on Learning Representations)
8. ImageNet: A large-scale hierarchical image database
9. Learning Multiple Layers of Features from Tiny Images
10. Going deeper with convolutions

Their papers

• Learning Object-Centric Representations of Multi-Object Scenes from Multiple Views (2021) — 62 citations