Stéphane Doncieux
Artificial Intelligence · 2008–2020
A researcher in the Science corpus: 6 papers; trusts 36 researchers and is trusted by 23 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 84 citations into it; #10,622 of 35,345 by trust here, #10,566 by citations
- Reinforcement Learning — 42 citations into it
- Computer Vision and Pattern Recognition — 29 citations into it; #10,061 of 21,575 by trust here, #14,478 by citations
- Aerospace Engineering — 17 citations into it; #2,141 of 6,421 by trust here, #3,519 by citations
- Computational Theory and Mathematics — 14 citations into it
- Mechanical Engineering — 14 citations into it
- Biomedical Engineering — 5 citations into it; #5,384 of 10,734 by trust here, #8,278 by citations
- Electrical and Electronic Engineering — 5 citations into it
Whom Stéphane Doncieux trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Kalyanmoy Deb
- Richard S. Sutton
- Kenneth O. Stanley
- David Nistér
- Geoffrey E. Hinton
- David G. Lowe
- J. Weng
- John Edwin Laird
- Pieter Abbeel
- Yoshua Bengio
Who trusts Stéphane Doncieux overall
- Jean-Baptiste Mouret
- Paul Tonelli
- Jeff Clune
- A. Irpan
- Mathieu Labbé
- Michael Milford
- Giseop Kim
- Dorian Gálvez-López
Papers from Stéphane Doncieux's perspective
Ordered by how strongly the researchers Stéphane Doncieux trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- Reinforcement Learning: An Introduction
Their papers
- The Surprising Creativity of Digital Evolution: A Collection of Anecdotes from the Evolutionary Computation and Artificial Life Research Communities (2018) — 317 citations
- Crossing the reality gap in evolutionary robotics by promoting transferable controllers (2010) — 138 citations
- Fast and Incremental Method for Loop-Closure Detection Using Bags of Visual Words (2008) — 564 citations
- Overcoming the bootstrap problem in evolutionary robotics using behavioral diversity (2009) — 127 citations
- The Transferability Approach: Crossing the Reality Gap in Evolutionary Robotics (2013) — 303 citations
- DREAM Architecture: a Developmental Approach to Open-Ended Learning in Robotics (2020) — 19 citations