Jake Goldenfein

Computer Vision and Pattern Recognition · 2019

A researcher in the Science corpus: 1 paper; trusts 7 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 5 citations into it; #18,221 of 21,575 by trust here, #21,103 by citations

Whom Jake Goldenfein trusts overall

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

1. Xiaolin Wu
2. Xi Zhang
3. Simon J. D. Prince
4. Yoshua Bengio
5. Alex Krizhevsky
6. Geoffrey E. Hinton
7. Yann LeCun
8. Alexander Todorov
9. Rob Kitchin
10. Hubert L. Dreyfus

Who trusts Jake Goldenfein overall

1. Abigail Z. Jacobs

Papers from Jake Goldenfein's perspective

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

Their papers

• The Profiling Potential of Computer Vision and the Challenge of Computational Empiricism (2019) — 24 citations