Kevin Chen

Computer Vision and Pattern Recognition · 2016–2021

A researcher in the Science corpus: 6 papers; trusts 551 researchers and is trusted by 453 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 183 citations into it; #1,976 of 21,575 by trust here, #3,166 by citations
• Artificial Intelligence — 140 citations into it; #27,353 of 35,345 by trust here, #23,077 by citations
• Reinforcement Learning — 79 citations into it
• Aerospace Engineering — 53 citations into it; #672 of 6,421 by trust here, #475 by citations
• Natural Language Processing — 43 citations into it
• Robotics & Control — 27 citations into it
• Model Architectures — 22 citations into it
• Control and Systems Engineering — 20 citations into it

Whom Kevin Chen trusts overall

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

1. Diederik P. Kingma
2. Geoffrey E. Hinton
3. Alex Krizhevsky
4. Ilya Sutskever
5. Yoshua Bengio
6. Kaiming He
7. Sepp Hochreiter
8. Ruslan Salakhutdinov
9. Jimmy Ba
10. Yann LeCun

Who trusts Kevin Chen overall

1. Heming Du
2. Christoph Feichtenhofer
3. Jiajun Wu
4. Yi Wu
5. Boyuan Chen
6. Jitendra Malik
7. Edward James Smith
8. Jie Yang
9. Julian Chibane
10. Fei Xia

Papers from Kevin Chen's perspective

Ordered by how strongly the researchers Kevin 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. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. ImageNet: A large-scale hierarchical image database
7. Gradient-based learning applied to document recognition
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• 3D-R2N2: A Unified Approach for Single and Multi-view 3D Object Reconstruction (2016) — 1,900 citations
• Lattice Long Short-Term Memory for Human Action Recognition (2017) — 174 citations
• A Behavioral Approach to Visual Navigation with Graph Localization Networks (2019) — 109 citations
• Learning Object-conditioned Exploration using Distributed Soft Actor Critic (2020) — 23 citations
• Learning Language-Conditioned Robot Behavior from Offline Data and Crowd-Sourced Annotation (2021) — 189 citations
• Topological Planning with Transformers for Vision-and-Language Navigation (2020) — 174 citations