James W. Pitton

Computer Vision and Pattern Recognition · 2016

A researcher in the Science corpus: 1 paper; trusts 9 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 10 citations into it
• Artificial Intelligence — 8 citations into it
• Computational Mechanics — 6 citations into it
• Model Architectures — 6 citations into it
• Optimization & Training — 5 citations into it

Whom James W. Pitton trusts overall

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

1. Robert Tibshirani
2. Yoshua Bengio
3. Mário A. T. Figueiredo
4. Xavier Glorot
5. Yann LeCun
6. John R. Hershey
7. Jason Tyler Rolfe

Papers from James W. Pitton's perspective

Ordered by how strongly the researchers James W. Pitton 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. Rectified Linear Units Improve Restricted Boltzmann Machines
4. Gradient-based learning applied to document recognition
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Understanding the difficulty of training deep feedforward neural networks
7. Long Short-Term Memory
8. Regression Shrinkage and Selection via the Lasso
9. Learning Multiple Layers of Features from Tiny Images
10. Attention is All you Need (Neural Information Processing Systems)

Their papers

• Interpretable Recurrent Neural Networks Using Sequential Sparse Recovery (2016) — 37 citations