Joshua I. Glaser

Artificial Intelligence · 2017

A researcher in the Science corpus: 1 paper; trusts 7 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 16 citations into it
• Optimization & Training — 9 citations into it
• Computer Vision and Pattern Recognition — 7 citations into it

Whom Joshua I. Glaser trusts overall

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

1. James Bergstra
2. Diederik P. Kingma
3. Yoshua Bengio
4. Chih-Jen Lin
5. Geoffrey E. Hinton
6. Alex Krizhevsky
7. Leo Breiman
8. Alex Smola
9. Radford M. Neal
10. Xavier Glorot

Papers from Joshua I. Glaser's perspective

Ordered by how strongly the researchers Joshua I. Glaser 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Long Short-Term Memory
5. Gradient-based learning applied to document recognition
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. Going deeper with convolutions
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Machine Learning for Neural Decoding (2017) — 315 citations