Austin Narcomey

Computer Vision and Pattern Recognition · 2019

A researcher in the Science corpus: 1 paper; trusts 23 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 31 citations into it
• Generative Models — 18 citations into it
• Evaluation & Benchmarks — 11 citations into it
• Computer Science Applications — 6 citations into it

Whom Austin Narcomey trusts overall

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

1. Alex Krizhevsky
2. Geoffrey E. Hinton
3. Yoshua Bengio
4. Diederik P. Kingma
5. Christian Szegedy
6. Radford M. Neal
7. Yann LeCun
8. Kaiming He
9. Ilya Sutskever
10. Jia Deng

Papers from Austin Narcomey's perspective

Ordered by how strongly the researchers Austin Narcomey 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. ImageNet: A large-scale hierarchical image database
4. Learning Multiple Layers of Features from Tiny Images
5. GENERATIVE ADVERSARIAL NETS
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. Gradient-based learning applied to document recognition
8. Long Short-Term Memory
9. Attention is All you Need (Neural Information Processing Systems)
10. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)

Their papers

• HYPE: A Benchmark for Human eYe Perceptual Evaluation of Generative Models (2019) — 136 citations