Michaël Perrot

Artificial Intelligence · 2015

A researcher in the Science corpus: 1 paper; trusts 36 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 12 citations into it
• Computer Vision and Pattern Recognition — 9 citations into it
• Representation & Self-Supervised Learning — 8 citations into it

Whom Michaël Perrot trusts overall

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

1. Aurélien Bellet
2. Kilian Q. Weinberger
3. Olivier Bousquet
4. Ilja Kuzborskij
5. Wolf Kienzle
6. Brian Kulis
7. Rong Jin
8. Qiong Cao
9. Boqing Gong
10. Amaury Habrard

Who trusts Michaël Perrot overall

1. Ilja Kuzborskij

Papers from Michaël Perrot's perspective

Ordered by how strongly the researchers Michaël Perrot 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. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. Going deeper with convolutions
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• A Theoretical Analysis of Metric Hypothesis Transfer Learning (2015) — 51 citations