Guillaume Flandin

Cognitive Neuroscience · 2002–2019

A researcher in the Science corpus: 10 papers; trusts 17 researchers and is trusted by 9 researchers here, as inferred from the citation graph.

Subfields

• Cognitive Neuroscience — 48 citations into it; #7,318 of 10,852 by trust here, #1,607 by citations
• Radiology, Nuclear Medicine and Imaging — 23 citations into it
• Statistics and Probability — 14 citations into it; #6,545 of 12,932 by trust here, #8,279 by citations
• Artificial Intelligence — 13 citations into it; #17,940 of 35,345 by trust here, #22,463 by citations
• Signal Processing — 10 citations into it
• Probabilistic & Bayesian Methods — 8 citations into it
• Biophysics — 7 citations into it
• Computer Vision and Pattern Recognition — 7 citations into it; #11,440 of 21,575 by trust here, #17,757 by citations

Whom Guillaume Flandin trusts overall

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

1. David L. Donoho
2. Stéphane Mallat
3. Karl J. Friston
4. W. D. Penny
5. Matthew J. Beal
6. Hagai Thomas Attias
7. Iain M. Johnstone
8. Alle Meije Wink
9. Anestis Antoniadis
10. Stefan J. Kiebel

Who trusts Guillaume Flandin overall

1. David M. Blei
2. Stefan J. Kiebel
3. Camelia M. Kuhnen
4. Jean Daunizeau
5. Alp Kucukelbir
6. Stephen M. Smith
7. John Thomas Ormerod
8. Karl J. Friston
9. Jon D. McAuliffe
10. Christophe L. M. Phillips

Papers from Guillaume Flandin's perspective

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

1. Variational algorithms for approximate Bayesian inference
2. Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper
3. A wavelet tour of signal processing
4. Estimating the Dimension of a Model
5. Dynamic causal modelling
6. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
7. A Theory for Multiresolution Signal Decomposition: The Wavelet Representation
8. Voxel-based morphometry--the methods.
9. Adapting to Unknown Smoothness via Wavelet Shrinkage
10. Variational free energy and the Laplace approximation

Their papers

• Bayesian fMRI data analysis with sparse spatial basis function priors (2007) — 113 citations
• Dopamine-dependent prediction errors underpin reward-seeking behaviour in humans (2006) — 1,566 citations
• The brain imaging data structure, a format for organizing and describing outputs of neuroimaging experiments (2016) — 1,663 citations
• Topological FDR for neuroimaging (2010) — 476 citations
• EEG-BIDS, an extension to the brain imaging data structure for electroencephalography (2019) — 389 citations
• MEG-BIDS, the brain imaging data structure extended to magnetoencephalography (2018)
• BIDS apps: Improving ease of use, accessibility, and reproducibility of neuroimaging data analysis methods (2016) — 311 citations
• EEG and MEG Data Analysis in SPM8 (2011) — 600 citations
• Multiple sparse priors for the M/EEG inverse problem (2008) — 627 citations
• Multivariate Model Specification for fMRI Data (2002) — 66 citations