Jamie Shotton

Computer Vision and Pattern Recognition · with Birch · 2023

A researcher in the Science corpus: 2 papers; trusts 48 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 59 citations into it
• Artificial Intelligence — 57 citations into it
• Generative Models — 23 citations into it

Whom Jamie Shotton trusts overall

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

1. Geoffrey E. Hinton
2. Diederik P. Kingma
3. Jonathan Ho
4. Alex Krizhevsky
5. Yoshua Bengio
6. Karen Simonyan

Papers from Jamie Shotton's perspective

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

1. Attention is All you Need (Neural Information Processing Systems)
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. ImageNet classification with deep convolutional neural networks
4. GENERATIVE ADVERSARIAL NETS
5. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. Long Short-Term Memory
8. Gradient-based learning applied to document recognition
9. ImageNet: A large-scale hierarchical image database
10. Et al

Their papers

• GAIA-1: A Generative World Model for Autonomous Driving (2023) — 613 citations
• Driving with LLMs: Fusing Object-Level Vector Modality for Explainable Autonomous Driving (2023) — 357 citations