Peiqiu Chen

Computer Vision and Pattern Recognition · with Wei · 2014–2019

A researcher in the Science corpus: 2 papers; trusts 120 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 34 citations into it; #19,313 of 21,575 by trust here, #16,367 by citations
• Artificial Intelligence — 33 citations into it; #31,455 of 35,345 by trust here, #25,040 by citations
• Representation & Self-Supervised Learning — 12 citations into it
• Meta & Continual Learning — 9 citations into it
• Model Architectures — 8 citations into it; #1,985 of 2,278 by trust here, #1,976 by citations
• Probabilistic & Bayesian Methods — 8 citations into it

Whom Peiqiu Chen trusts overall

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

1. Geoffrey E. Hinton
2. Alex Krizhevsky
3. Yann LeCun
4. Diederik P. Kingma
5. Yoshua Bengio
6. Kaiming He
7. Ilya Sutskever
8. Radford M. Neal
9. Matthew D. Zeiler
10. Marc'Aurelio Ranzato

Who trusts Peiqiu Chen overall

1. Hossein Gholamalinezhad

Papers from Peiqiu Chen's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. ImageNet: A large-scale hierarchical image database
5. Gradient-based learning applied to document recognition
6. Attention is All you Need (Neural Information Processing Systems)
7. Long Short-Term Memory
8. Learning Multiple Layers of Features from Tiny Images
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Overcoming Catastrophic Forgetting by Bayesian Generative Regularization (2019) — 19 citations
• Mixed Pooling for Convolutional Neural Networks (2014) — 425 citations