Jonathan Viquerat

Artificial Intelligence · 2019

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

Subfields

• Artificial Intelligence — 29 citations into it
• Optimization & Training — 6 citations into it

Whom Jonathan Viquerat trusts overall

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

1. Nikolaus Hansen
2. Richard S. Sutton
3. Sepp Hochreiter
4. John Schulman
5. Ronald J. Williams
6. J. Urgen Schmidhuber
7. G. Tesauro
8. Geoffrey E. Hinton

Who trusts Jonathan Viquerat overall

1. Ji-chao Li

Papers from Jonathan Viquerat's perspective

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

1. Long Short-Term Memory
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. ImageNet classification with deep convolutional neural networks
4. Asynchronous Methods for Deep Reinforcement Learning
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Gradient-based learning applied to document recognition
7. Proximal Policy Optimization Algorithms (arXiv.org)
8. Attention is All you Need (Neural Information Processing Systems)
9. Learning Multiple Layers of Features from Tiny Images
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• A review on Deep Reinforcement Learning for Fluid Mechanics (2019) — 330 citations