Loïc Pauletto

Artificial Intelligence · 2022

A researcher in the Science corpus: 1 paper; trusts 7 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 38 citations into it
• Computer Vision and Pattern Recognition — 23 citations into it
• Representation & Self-Supervised Learning — 16 citations into it
• Natural Language Processing — 6 citations into it
• Optimization & Training — 5 citations into it

Whom Loïc Pauletto trusts overall

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

1. Alex Krizhevsky
2. Thorsten Joachims
3. Dong-Hyun Lee
4. Qizhe Xie
5. Geoffrey E. Hinton
6. Yoshua Bengio
7. Kamal Nigam
8. Samuli Laine
9. Diederik P. Kingma

Papers from Loïc Pauletto's perspective

Ordered by how strongly the researchers Loïc Pauletto 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. Learning Multiple Layers of Features from Tiny Images
4. Gradient-based learning applied to document recognition
5. ImageNet: A large-scale hierarchical image database
6. Attention is All you Need (Neural Information Processing Systems)
7. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
8. Long Short-Term Memory
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. Going deeper with convolutions

Their papers

• Self-Training: A Survey (2022) — 195 citations