Thomas Boquet

Artificial Intelligence · 2017–2018

A researcher in the Science corpus: 2 papers; trusts 24 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 32 citations into it
• Computer Vision and Pattern Recognition — 14 citations into it
• Probabilistic & Bayesian Methods — 13 citations into it
• Generative Models — 7 citations into it
• Optimization & Training — 7 citations into it

Whom Thomas Boquet trusts overall

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

1. Diederik P. Kingma
2. Geoffrey E. Hinton
3. Jimmy Ba
4. Charles Blundell
5. Kaiming He
6. Yoshua Bengio
7. Yarin Gal
8. Alex Krizhevsky
9. Max Welling
10. Yann LeCun

Who trusts Thomas Boquet overall

1. Chelsea Finn

Papers from Thomas Boquet's perspective

Ordered by how strongly the researchers Thomas Boquet trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
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. GENERATIVE ADVERSARIAL NETS
8. ImageNet: A large-scale hierarchical image database
9. Learning Multiple Layers of Features from Tiny Images
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Deep Prior (2017) — 7 citations
• Uncertainty in Multitask Transfer Learning (2018) — 21 citations