Forrest Huang

Computer Vision and Pattern Recognition · 2018–2019

A researcher in the Science corpus: 2 papers; trusts 250 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 43 citations into it; #17,953 of 21,575 by trust here, #16,787 by citations
• Artificial Intelligence — 26 citations into it
• Representation & Self-Supervised Learning — 22 citations into it; #2,772 of 3,145 by trust here, #3,009 by citations
• Signal Processing — 8 citations into it
• Information Retrieval & Search — 7 citations into it
• Media Technology — 7 citations into it
• Model Architectures — 5 citations into it

Whom Forrest Huang trusts overall

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

1. Alex Krizhevsky
2. Geoffrey E. Hinton
3. L. V. D. van der Maaten
4. Kaiming He
5. Yann LeCun
6. Yoshua Bengio
7. Karen Simonyan
8. David G. Lowe
9. Sam T. Roweis
10. Jia Deng

Who trusts Forrest Huang overall

1. Dmitry Kobak
2. Anna C. Belkina

Papers from Forrest Huang's perspective

Ordered by how strongly the researchers Forrest Huang 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. Gradient-based learning applied to document recognition
4. ImageNet: A large-scale hierarchical image database
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
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. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• GPU accelerated t-distributed stochastic neighbor embedding (2019) — 79 citations
• T-SNE-CUDA: GPU-Accelerated T-SNE and its Applications to Modern Data (2018) — 106 citations