Charles Bouveyron

Artificial Intelligence · 2006–2014

A researcher in the Science corpus: 3 papers; trusts 67 researchers and is trusted by 17 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 27 citations into it; #7,723 of 35,345 by trust here, #15,004 by citations
• Statistics and Probability — 22 citations into it
• Computer Vision and Pattern Recognition — 13 citations into it; #9,168 of 21,575 by trust here, #15,162 by citations
• Probabilistic & Bayesian Methods — 8 citations into it
• Representation & Self-Supervised Learning — 6 citations into it
• Computational Theory and Mathematics — 5 citations into it
• Statistical Learning Theory — 5 citations into it

Whom Charles Bouveyron trusts overall

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

1. Adrian E. Raftery
2. Geoffrey J. McLachlan
3. Peter J. Bickel
4. David G. Lowe
5. P. Deb
6. Noureddine El Karoui
7. R. Fisher
8. Donald B. Rubin
9. Arthur P. Dempster
10. Teuvo Kohonen

Who trusts Charles Bouveyron overall

1. Benoît Frénay
2. J. Jacques
3. Sylvain Calinon
4. Alexander Rainer Tassilo Gepperth
5. Dennis Wei
6. Cristian Preda
7. Angela Montanari
8. Michel Verleysen
9. Paul David McNicholas
10. Jakramate Bootkrajang

Papers from Charles Bouveyron's perspective

Ordered by how strongly the researchers Charles Bouveyron 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. Gradient-based learning applied to document recognition
5. ImageNet: A large-scale hierarchical image database
6. Long Short-Term Memory
7. Attention is All you Need (Neural Information Processing Systems)
8. Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Model-based clustering of high-dimensional data: A review (2014) — 473 citations
• Robust supervised classification with mixture models: Learning from data with uncertain labels (2009) — 142 citations
• High-dimensional data clustering (2006) — 426 citations