Jacob Byerly

2020

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

Whom Jacob Byerly trusts overall

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

1. Robert Hecht-Nielsen
2. Florian Schroff
3. Rong Chen

Papers from Jacob Byerly's perspective

Ordered by how strongly the researchers Jacob Byerly trusts endorse each paper. Same corpus, a different order for every researcher.

1. Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation
2. ImageNet classification with deep convolutional neural networks
3. Mastering the game of Go with deep neural networks and tree search
4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
5. Gradient-based learning applied to document recognition
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. Long Short-Term Memory
8. FaceNet: A unified embedding for face recognition and clustering
9. Attention is All you Need (Neural Information Processing Systems)
10. A Survey on Transfer Learning

Their papers

• A Review of Deep Learning Methods for Antibodies (2020) — 84 citations