Peter U. Diehl

Electrical and Electronic Engineering · 2015

A researcher in the Science corpus: 2 papers; trusts 38 researchers and is trusted by 34 researchers here, as inferred from the citation graph.

Subfields

• Electrical and Electronic Engineering — 26 citations into it; #838 of 16,539 by trust here, #5,516 by citations
• Cognitive Neuroscience — 20 citations into it; #941 of 10,852 by trust here, #2,998 by citations
• Cellular and Molecular Neuroscience — 14 citations into it; #375 of 2,998 by trust here, #1,976 by citations
• Artificial Intelligence — 10 citations into it
• Computer Vision and Pattern Recognition — 9 citations into it
• Model Architectures — 6 citations into it

Whom Peter U. Diehl trusts overall

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

1. Daniel Neil
2. David E. Rumelhart
3. Geoffrey E. Hinton
4. Yann LeCun
5. Shih-Chii Liu
6. J. Urgen Schmidhuber
7. Paul A. Merolla
8. Yoshua Bengio
9. Wei Zhang
10. Rasmus Berg Palm

Who trusts Peter U. Diehl overall

1. Kaushik Roy
2. S. R. Kheradpisheh
3. Bing Han
4. Junhaeng Lee
5. Michael Pfeiffer
6. Seijoon Kim
7. Gopalakrishnan Srinivasan
8. Timothy Tadros
9. Nitin Rathi
10. Yujie Wu

Papers from Peter U. Diehl's perspective

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

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

Their papers

• Fast-classifying, high-accuracy spiking deep networks through weight and threshold balancing (2015) — 1,067 citations
• Unsupervised learning of digit recognition using spike-timing-dependent plasticity (2015) — 1,436 citations