Hélène Paugam-Moisy

Representation & Self-Supervised Learning · 2011

A researcher in the Science corpus: 1 paper; trusts 21 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Representation & Self-Supervised Learning — 16 citations into it
• Computer Vision and Pattern Recognition — 14 citations into it
• Artificial Intelligence — 13 citations into it
• Probabilistic & Bayesian Methods — 7 citations into it
• Model Architectures — 6 citations into it

Whom Hélène Paugam-Moisy trusts overall

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

1. Geoffrey E. Hinton
2. Yoshua Bengio
3. Alex Krizhevsky
4. Marc'Aurelio Ranzato
5. Yann LeCun
6. Honglak Lee
7. Ruslan Salakhutdinov
8. Ronan Collobert
9. Koray Kavukcuoglu
10. Radford M. Neal

Papers from Hélène Paugam-Moisy's perspective

Ordered by how strongly the researchers Hélène Paugam-Moisy 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. Gradient-based learning applied to document recognition
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Attention is All you Need (Neural Information Processing Systems)
6. Long Short-Term Memory
7. Learning Multiple Layers of Features from Tiny Images
8. ImageNet: A large-scale hierarchical image database
9. ImageNet Large Scale Visual Recognition Challenge
10. Rectified Linear Units Improve Restricted Boltzmann Machines

Their papers

• An Introduction to Deep Learning (2011) — 32 citations