Benoît Girard

Cognitive Neuroscience · 2018–2020

A researcher in the Science corpus: 2 papers; trusts 13 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Cognitive Neuroscience — 50 citations into it
• Artificial Intelligence — 48 citations into it
• Reinforcement Learning — 43 citations into it
• Cellular and Molecular Neuroscience — 28 citations into it
• Neuroscience — 17 citations into it

Whom Benoît Girard trusts overall

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

1. Richard S. Sutton
2. Ben J. A. Kröse
3. Peter S. Dayan
4. György Buzsáki
5. Brad E. Pfeiffer
6. David J. Foster
7. Mehdi Khamassi
8. Andrew W. Moore

Papers from Benoît Girard's perspective

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

1. Reinforcement Learning: An Introduction
2. Proximal Policy Optimization Algorithms (arXiv.org)
3. ImageNet classification with deep convolutional neural networks
4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
5. Gradient-based learning applied to document recognition
6. A Survey on Transfer Learning
7. Long Short-Term Memory
8. FeUdal Networks for Hierarchical Reinforcement Learning
9. Learning from delayed rewards
10. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)

Their papers

• DREAM Architecture: a Developmental Approach to Open-Ended Learning in Robotics (2020) — 19 citations
• Hippocampal replays under the scrutiny of reinforcement learning models. (2018) — 42 citations