Matthew Bowers

Artificial Intelligence · 2022

A researcher in the Science corpus: 1 paper; trusts 14 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 22 citations into it
• Large Language Models — 9 citations into it
• Computer Vision and Pattern Recognition — 6 citations into it
• Natural Language Processing — 6 citations into it

Whom Matthew Bowers trusts overall

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

1. Geoffrey E. Hinton
2. Diederik P. Kingma
3. Ilya Sutskever
4. Jimmy Ba
5. Ilya Loshchilov
6. Yoshua Bengio
7. Alex Krizhevsky
8. Oriol Vinyals
9. Timo Schick
10. Stanislas Polu

Papers from Matthew Bowers's perspective

Ordered by how strongly the researchers Matthew Bowers 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. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. ImageNet classification with deep convolutional neural networks
4. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
9. Learning Multiple Layers of Features from Tiny Images
10. Distilling the Knowledge in a Neural Network (arXiv.org)

Their papers

• Language Models Can Teach Themselves to Program Better (2022) — 103 citations