Teddy Koker

Computer Vision and Pattern Recognition · 2021

A researcher in the Science corpus: 1 paper; trusts 185 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 44 citations into it
• Representation & Self-Supervised Learning — 38 citations into it
• Artificial Intelligence — 37 citations into it
• Optimization & Training — 5 citations into it

Whom Teddy Koker trusts overall

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

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

Papers from Teddy Koker's perspective

Ordered by how strongly the researchers Teddy Koker 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. ImageNet: A large-scale hierarchical image database
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. Long Short-Term Memory
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. ImageNet Large Scale Visual Recognition Challenge

Their papers

• AAVAE: Augmentation-Augmented Variational Autoencoders (2021) — 11 citations