Charlotte Frenkel

Electrical and Electronic Engineering · 2018

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

• Electrical and Electronic Engineering — 21 citations into it
• Cognitive Neuroscience — 13 citations into it

Whom Charlotte Frenkel trusts overall

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

1. Yann LeCun
2. Romain Brette
3. Eugene M. Izhikevich
4. Saber Moradi
5. Matthieu Courbariaux
6. Wulfram Gerstner
7. Bodo Rueckauer
8. Shih-Chii Liu
9. Corinna Cortes
10. Ning Qiao

Papers from Charlotte Frenkel's perspective

Ordered by how strongly the researchers Charlotte Frenkel 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. Learning Multiple Layers of Features from Tiny Images
5. Long Short-Term Memory
6. Going deeper with convolutions
7. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
8. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
9. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• A 0.086-mm$^2$ 12.7-pJ/SOP 64k-Synapse 256-Neuron Online-Learning Digital Spiking Neuromorphic Processor in 28-nm CMOS (2018) — 312 citations