Lauren Brown

Computer Vision and Pattern Recognition · 2023

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

Subfields

• Computer Vision and Pattern Recognition — 27 citations into it
• Evaluation & Benchmarks — 7 citations into it

Whom Lauren Brown trusts overall

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

1. Diederik P. Kingma
2. Geoffrey E. Hinton
3. Alex Krizhevsky
4. Yoshua Bengio
5. Andrew Y. Ng
6. Li Deng
7. Ilya Sutskever
8. Yann LeCun
9. Alec Radford
10. Kaiming He

Papers from Lauren Brown's perspective

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

Their papers

• AI Art and its Impact on Artists (2023) — 329 citations