Noah Golmant

Computer Vision and Pattern Recognition · 2017–2018

A researcher in the Science corpus: 2 papers; trusts 58 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 44 citations into it
• Artificial Intelligence — 34 citations into it
• Optimization & Training — 15 citations into it
• Model Architectures — 13 citations into it

Whom Noah Golmant trusts overall

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

1. Alex Krizhevsky
2. Yoshua Bengio
3. Kaiming He
4. L. Eon Bottou
5. Karen Simonyan
6. Geoffrey E. Hinton
7. Yann LeCun
8. Sepp Hochreiter
9. J. Urgen Schmidhuber
10. Andrew Zisserman

Who trusts Noah Golmant overall

1. Chaoyue Liu
2. Christopher J. Shallue
3. Charles H. Martin

Papers from Noah Golmant's perspective

Ordered by how strongly the researchers Noah Golmant 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. Long Short-Term Memory
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. ImageNet: A large-scale hierarchical image database
6. Gradient-based learning applied to document recognition
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

• Shift: A Zero FLOP, Zero Parameter Alternative to Spatial Convolutions (2017) — 401 citations
• On the Computational Inefficiency of Large Batch Sizes for Stochastic Gradient Descent (2018) — 82 citations