Galen Chuang

Computer Vision and Pattern Recognition · 2018

A researcher in the Science corpus: 2 papers; trusts 243 researchers and is trusted by 9 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 63 citations into it; #12,048 of 21,575 by trust here, #9,563 by citations
• Artificial Intelligence — 61 citations into it
• Multimodal Learning — 43 citations into it; #395 of 1,211 by trust here, #685 by citations
• Speech & Audio — 34 citations into it; #543 of 1,076 by trust here, #900 by citations
• Signal Processing — 33 citations into it; #3,966 of 7,572 by trust here, #2,114 by citations
• Natural Language Processing — 20 citations into it
• Representation & Self-Supervised Learning — 13 citations into it; #1,970 of 3,145 by trust here, #1,754 by citations
• Model Architectures — 8 citations into it

Whom Galen Chuang trusts overall

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

1. Geoffrey E. Hinton
2. Yoshua Bengio
3. Karen Simonyan
4. Alex Krizhevsky
5. Kaiming He
6. Antonio Torralba
7. David F. Harwath
8. Yann LeCun
9. Diederik P. Kingma
10. Herman Kamper

Who trusts Galen Chuang overall

1. David F. Harwath
2. Grzegorz Chrupała
3. James R. Glass
4. Emmanuel Azuh
5. Wei-Ning Hsu
6. William N. Havard
7. Marcely Zanon Boito
8. Herman Kamper

Papers from Galen Chuang's perspective

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

• Jointly Discovering Visual Objects and Spoken Words from Raw Sensory Input (2018) — 213 citations
• Vision as an Interlingua: Learning Multilingual Semantic Embeddings of Untranscribed Speech (2018) — 61 citations