Nicolas Perrin

Artificial Intelligence · with Sigaud · 2016–2019

A researcher in the Science corpus: 3 papers; trusts 25 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 39 citations into it
• Reinforcement Learning — 28 citations into it
• Control and Systems Engineering — 10 citations into it

Whom Nicolas Perrin trusts overall

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

1. Ben J. A. Kröse
2. Richard S. Sutton
3. David Silver
4. Volodymyr Mnih
5. Hado van Hasselt
6. Tuomas Haarnoja
7. John N. Tsitsiklis
8. Justin A. Boyan
9. Geoffrey E. Hinton
10. Martin A. Riedmiller

Papers from Nicolas Perrin's perspective

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

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

Their papers

• Learning Compositional Neural Programs with Recursive Tree Search and Planning (2019) — 43 citations
• The problem with DDPG: understanding failures in deterministic environments with sparse rewards (2019) — 73 citations
• Fast diffeomorphic matching to learn globally asymptotically stable nonlinear dynamical systems (2016) — 66 citations