Charlie Blake

Artificial Intelligence · 2023

A researcher in the Science corpus: 1 paper; trusts 29 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 39 citations into it
• Computer Vision and Pattern Recognition — 19 citations into it
• Optimization & Training — 13 citations into it
• Model Architectures — 10 citations into it
• Natural Language Processing — 9 citations into it

Whom Charlie Blake trusts overall

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

1. Diederik P. Kingma
2. Kaiming He
3. Yoshua Bengio
4. Jimmy Ba
5. Geoffrey E. Hinton
6. Alex Krizhevsky
7. Xavier Glorot
8. Sara Hooker
9. Yann LeCun
10. Ilya Sutskever

Papers from Charlie Blake's perspective

Ordered by how strongly the researchers Charlie Blake 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. ImageNet classification with deep convolutional neural networks
3. Attention is All you Need (Neural Information Processing Systems)
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. ImageNet: A large-scale hierarchical image database
7. Gradient-based learning applied to document recognition
8. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Unit Scaling: Out-of-the-Box Low-Precision Training (2023) — 20 citations