John Rogers-Lee

Artificial Intelligence · 2018

A researcher in the Science corpus: 1 paper; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 14 citations into it
• Probabilistic & Bayesian Methods — 10 citations into it
• Optimization & Training — 5 citations into it

Whom John Rogers-Lee trusts overall

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

1. Diederik P. Kingma
2. Tim Salimans
3. Geoffrey E. Hinton

Papers from John Rogers-Lee's perspective

Ordered by how strongly the researchers John Rogers-Lee trusts endorse each paper. Same corpus, a different order for every researcher.

1. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
2. Auto-Encoding Variational Bayes (International Conference on Learning Representations)
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. ImageNet classification with deep convolutional neural networks
5. Gradient-based learning applied to document recognition
6. Learning Multiple Layers of Features from Tiny Images
7. Attention is All you Need (Neural Information Processing Systems)
8. U-Net: Convolutional Networks for Biomedical Image Segmentation (International Conference on Medical Image Computing and Computer-Assisted Intervention)
9. ImageNet: A large-scale hierarchical image database
10. Going deeper with convolutions

Their papers

• Distributed Weight Consolidation: A Brain Segmentation Case Study (2018) — 28 citations