Peirong Liu

Artificial Intelligence · 2020

A researcher in the Science corpus: 1 paper; trusts 51 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 24 citations into it
• Computer Vision and Pattern Recognition — 24 citations into it
• Evaluation & Benchmarks — 9 citations into it
• Probabilistic & Bayesian Methods — 5 citations into it

Whom Peirong Liu trusts overall

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

1. Diederik P. Kingma
2. Kaiming He
3. Geoffrey E. Hinton
4. J. Platt
5. Gabriel J. Brostow
6. Alex Krizhevsky
7. Yoshua Bengio
8. Yann LeCun
9. Bianca Zadrozny
10. Jimmy Ba

Papers from Peirong Liu's perspective

Ordered by how strongly the researchers Peirong Liu 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. ImageNet: A large-scale hierarchical image database
6. Long Short-Term Memory
7. Attention is All you Need (Neural Information Processing Systems)
8. Learning Multiple Layers of Features from Tiny Images
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• Local Temperature Scaling for Probability Calibration (2020) — 122 citations