Pierre Fournier

Artificial Intelligence · 2018

A researcher in the Science corpus: 2 papers; trusts 8 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 44 citations into it
• Reinforcement Learning — 40 citations into it
• Control and Systems Engineering — 12 citations into it
• Meta & Continual Learning — 6 citations into it

Whom Pierre Fournier trusts overall

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

1. Richard S. Sutton
2. Pierre-Yves Oudeyer
3. Adrien Baranes
4. Andrew Barto
5. J. Urgen Schmidhuber
6. Scott Fujimoto
7. Tom Schaul
8. David Held
9. Marcin Andrychowicz
10. Timothy P. Lillicrap

Who trusts Pierre Fournier overall

1. Sébastien Forestier
2. Lisa Lee
3. Kalifou René Traoré
4. Vitchyr H. Pong

Papers from Pierre Fournier's perspective

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

1. Reinforcement Learning: An Introduction
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. ImageNet classification with deep convolutional neural networks
4. Continuous control with deep reinforcement learning (International Conference on Learning Representations)
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Gradient-based learning applied to document recognition
7. Long Short-Term Memory
8. Attention is All you Need (Neural Information Processing Systems)
9. Hindsight Experience Replay
10. Asynchronous Methods for Deep Reinforcement Learning

Their papers

• CURIOUS: Intrinsically Motivated Modular Multi-Goal Reinforcement Learning (2018) — 191 citations
• CURIOUS: Intrinsically Motivated Multi-Task, Multi-Goal Reinforcement Learning (2018) — 41 citations