Freddie Bickford-Smith

Artificial Intelligence · 2023

A researcher in the Science corpus: 1 paper; trusts 11 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 33 citations into it
• Computer Vision and Pattern Recognition — 17 citations into it
• Meta & Continual Learning — 14 citations into it
• Probabilistic & Bayesian Methods — 11 citations into it
• Optimization & Training — 8 citations into it

Whom Freddie Bickford-Smith trusts overall

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

1. Lehel Csató
2. Geoffrey E. Hinton
3. Masa-aki Sato
4. Dong Yin
5. Alex Krizhevsky
6. Yoshua Bengio
7. Diederik P. Kingma
8. Thang D. Bui
9. David Lopez-Paz
10. Yann LeCun

Papers from Freddie Bickford-Smith's perspective

Ordered by how strongly the researchers Freddie Bickford-Smith 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. Gradient-based learning applied to document recognition
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Learning Multiple Layers of Features from Tiny Images
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. Long Short-Term Memory
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Continual Learning via Sequential Function-Space Variational Inference (2023) — 59 citations