Ellis Brown

Computer Vision and Pattern Recognition · 2023–2024

A researcher in the Science corpus: 2 papers; trusts 176 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 119 citations into it
• Artificial Intelligence — 111 citations into it
• Generative Models — 31 citations into it
• Probabilistic & Bayesian Methods — 11 citations into it
• Biophysics — 5 citations into it

Whom Ellis Brown trusts overall

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

1. Geoffrey E. Hinton
2. Kaiming He
3. Diederik P. Kingma
4. Alex Krizhevsky
5. Yann LeCun
6. Yoshua Bengio
7. Ross B. Girshick
8. Ilya Sutskever
9. Karen Simonyan
10. Andrew Zisserman

Papers from Ellis Brown's perspective

Ordered by how strongly the researchers Ellis Brown 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. ImageNet: A large-scale hierarchical image database
6. Long Short-Term Memory
7. ImageNet Large Scale Visual Recognition Challenge
8. Gradient-based learning applied to document recognition
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Cambrian-1: A Fully Open, Vision-Centric Exploration of Multimodal LLMs (2024) — 900 citations
• Your Diffusion Model is Secretly a Zero-Shot Classifier (2023) — 371 citations