Samson Yu

Computer Vision and Pattern Recognition · 2020–2021

A researcher in the Science corpus: 4 papers; trusts 473 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 133 citations into it; #14,472 of 21,575 by trust here, #13,815 by citations
• Artificial Intelligence — 99 citations into it; #23,443 of 35,345 by trust here, #20,836 by citations
• Reinforcement Learning — 42 citations into it
• Aerospace Engineering — 33 citations into it
• Control and Systems Engineering — 17 citations into it
• Evaluation & Benchmarks — 16 citations into it
• Developmental and Educational Psychology — 10 citations into it
• Model Architectures — 8 citations into it

Whom Samson Yu trusts overall

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

1. Geoffrey E. Hinton
2. Kaiming He
3. Yoshua Bengio
4. Diederik P. Kingma
5. Alex Krizhevsky
6. Ronald J. Williams
7. Yann LeCun
8. Ross B. Girshick
9. Ilya Sutskever
10. Karen Simonyan

Who trusts Samson Yu overall

1. Jiafei Duan

Papers from Samson Yu's perspective

Ordered by how strongly the researchers Samson Yu 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. Attention is All you Need (Neural Information Processing Systems)
5. ImageNet: A large-scale hierarchical image database
6. Long Short-Term Memory
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

• A Survey of Embodied AI: From Simulators to Research Tasks (2021) — 536 citations
• PIP: Physical Interaction Prediction via Mental Imagery with Span Selection (2021) — 7 citations
• SPACE: A Simulator for Physical Interactions and Causal Learning in 3D Environments (2021) — 16 citations
• ActioNet: An Interactive End-To-End Platform For Task-Based Data Collection And Augmentation In 3D Environment (2020) — 9 citations