Jonathan Deaton

Artificial Intelligence · 2020–2021

A researcher in the Science corpus: 2 papers; trusts 5 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 111 citations into it
• Computer Vision and Pattern Recognition — 59 citations into it

Whom Jonathan Deaton trusts overall

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

1. Kaiming He
2. Geoffrey E. Hinton

Papers from Jonathan Deaton's perspective

Ordered by how strongly the researchers Jonathan Deaton 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. Long Short-Term Memory
3. ImageNet: A large-scale hierarchical image database
4. ImageNet classification with deep convolutional neural networks
5. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
6. Attention is All you Need (Neural Information Processing Systems)
7. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
8. Gradient-based learning applied to document recognition
9. ImageNet Large Scale Visual Recognition Challenge
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Underspecification Presents Challenges for Credibility in Modern Machine Learning (2020) — 897 citations
• Big Self-Supervised Models Advance Medical Image Classification (2021) — 741 citations