Sébastien Rebecchi

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 Sébastien Rebecchi trusts overall

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

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

Papers from Sébastien Rebecchi's perspective

Ordered by how strongly the researchers Sébastien Rebecchi 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Gradient-based learning applied to document recognition
5. Attention is All you Need (Neural Information Processing Systems)
6. Long Short-Term Memory
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. ImageNet Large Scale Visual Recognition Challenge
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

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