Thomas Pfeil

Electrical and Electronic Engineering · 2018

A researcher in the Science corpus: 1 paper; trusts 71 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

• Electrical and Electronic Engineering — 57 citations into it; #5,224 of 16,539 by trust here, #11,313 by citations
• Cognitive Neuroscience — 42 citations into it
• Artificial Intelligence — 34 citations into it
• Cellular and Molecular Neuroscience — 22 citations into it; #1,004 of 2,998 by trust here, #2,325 by citations
• Computer Vision and Pattern Recognition — 22 citations into it
• Neuroscience — 12 citations into it
• Efficiency & Compression — 9 citations into it
• Model Architectures — 9 citations into it

Whom Thomas Pfeil trusts overall

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

1. Yoshua Bengio
2. S. Furber
3. Geoffrey E. Hinton
4. Alex Krizhevsky
5. Yann LeCun
6. Chris Eliasmith
7. Hesham Mostafa
8. Daniel Neil
9. Kwabena A. Boahen
10. Matthieu Courbariaux

Who trusts Thomas Pfeil overall

1. Friedemann Zenke
2. Benjamin Cramer
3. Aboozar Taherkhani
4. Tim P. Vogels

Papers from Thomas Pfeil's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Gradient-based learning applied to document recognition
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Long Short-Term Memory
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Learning Multiple Layers of Features from Tiny Images
7. ImageNet Large Scale Visual Recognition Challenge
8. ImageNet: A large-scale hierarchical image database
9. Attention is All you Need (Neural Information Processing Systems)
10. Going deeper with convolutions

Their papers

• Deep Learning With Spiking Neurons: Opportunities and Challenges (2018) — 750 citations