George D. Webster

Signal Processing · 2016

A researcher in the Science corpus: 1 paper; trusts 6 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Signal Processing — 8 citations into it
• Computer Networks and Communications — 7 citations into it
• Artificial Intelligence — 6 citations into it

Whom George D. Webster trusts overall

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

1. Yoshua Bengio
2. Geoffrey E. Hinton
3. Roberto Perdisci
4. Joshua Saxe

Papers from George D. Webster's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Dropout: a simple way to prevent neural networks from overfitting
3. Et al
4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
5. Gradient-based learning applied to document recognition
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. Learning Deep Architectures for AI
8. Long Short-Term Memory
9. Attention is All you Need (Neural Information Processing Systems)
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Deep Learning for Classification of Malware System Call Sequences (2016) — 528 citations