Lawrence Cayton

Computer Vision and Pattern Recognition · 2005–2007

A researcher in the Science corpus: 2 papers; trusts 11 researchers and is trusted by 27 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 9 citations into it
• Artificial Intelligence — 7 citations into it
• Computational Theory and Mathematics — 5 citations into it

Whom Lawrence Cayton trusts overall

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

1. Christoph Helmberg
2. Mikhail Belkin
3. Partha Niyogi
4. Mayur Datar
5. Kilian Q. Weinberger
6. Lawrence K. Saul
7. Vin de Silva
8. Kenneth L. Clarkson
9. S. Omohundro
10. Josh Tenenbaum

Who trusts Lawrence Cayton overall

1. Yoshua Bengio
2. Salah Rifai
3. Alexej Klushyn
4. Limin Sun
5. Jun Wang
6. Yann Dauphin
7. Pascal Vincent
8. Antonio Criminisi
9. Aaron C. Courville
10. Guillaume Alain

Papers from Lawrence Cayton's perspective

Ordered by how strongly the researchers Lawrence Cayton trusts endorse each paper. Same corpus, a different order for every researcher.

1. Gradient-based learning applied to document recognition
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. ImageNet classification with deep convolutional neural networks
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. Going deeper with convolutions

Their papers

• A learning framework for nearest neighbor search (2007) — 40 citations
• Algorithms for manifold learning (2005) — 404 citations