Adrien Baranes

Artificial Intelligence · 2009–2014

A researcher in the Science corpus: 9 papers; trusts 81 researchers and is trusted by 54 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 111 citations into it; #3,434 of 35,345 by trust here, #6,796 by citations
• Cognitive Neuroscience — 83 citations into it; #5,558 of 10,852 by trust here, #7,860 by citations
• Reinforcement Learning — 69 citations into it
• Control and Systems Engineering — 49 citations into it; #316 of 8,257 by trust here, #508 by citations
• Computer Vision and Pattern Recognition — 30 citations into it
• Cognitive Science & Psychology — 23 citations into it
• Developmental and Educational Psychology — 23 citations into it
• Social Psychology — 23 citations into it

Whom Adrien Baranes trusts overall

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

1. J. Urgen Schmidhuber
2. Pierre-Yves Oudeyer
3. Richard S. Sutton
4. Sylvain Calinon
5. D. Berlyne
6. Jan Peters
7. Stefan Schaal
8. Andrew Barto
9. Edward L. Deci
10. Sethu Vijayakumar

Who trusts Adrien Baranes overall

1. Pierre-Yves Oudeyer
2. Manuel Lopes
3. Sao Mai Nguyen
4. Cédric Colas
5. Sébastien Forestier
6. Olivier Sigaud
7. Gianluca Baldassarre
8. Todd Hester
9. Clément Moulin-Frier
10. J. Urgen Schmidhuber

Papers from Adrien Baranes's perspective

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

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

Their papers

• Active learning of inverse models with intrinsically motivated goal exploration in robots (2013) — 458 citations
• Intrinsically motivated goal exploration for active motor learning in robots: A case study (2010) — 113 citations
• Intrinsically Motivated Learning of Real-World Sensorimotor Skills with Developmental Constraints (2013) — 78 citations
• R-IAC: Robust Intrinsically Motivated Exploration and Active Learning (2009) — 150 citations
• The interaction of maturational constraints and intrinsic motivations in active motor development (2011) — 29 citations
• Information seeking, curiosity and attention: computational and neural mechanisms (2013) — 115 citations
• The effects of task difficulty, novelty and the size of the search space on intrinsically motivated exploration (2014) — 89 citations
• Bootstrapping intrinsically motivated learning with human demonstration (2011) — 26 citations
• Incremental local online Gaussian Mixture Regression for imitation learning of multiple tasks (2010) — 92 citations