| EM procedures using mean field-like approximations for Markov model-based image segmentation G Celeux, F Forbes, N Peyrard Pattern recognition 36 (1), 131-144, 2003 | 443 | 2003 |
| Hidden Markov random field model selection criteria based on mean field-like approximations F Forbes, N Peyrard IEEE Transactions on Pattern Analysis and Machine Intelligence 25 (9), 1089-1101, 2003 | 167 | 2003 |
| Learning ecological networks from next-generation sequencing data C Vacher, A Tamaddoni-Nezhad, S Kamenova, N Peyrard, Y Moalic, ... Advances in ecological research 54, 1-39, 2016 | 128 | 2016 |
| There's no harm in having too much: a comprehensive toolbox of methods in trophic ecology N Majdi, N Hette-Tronquart, E Auclair, A Bec, T Chouvelon, B Cognie, ... Food webs 17, e00100, 2018 | 72 | 2018 |
| Modelling interaction networks for enhanced ecosystem services in agroecosystems P Tixier, N Peyrard, JN Aubertot, S Gaba, J Radoszycki, G Caron-Lormier, ... Advances in Ecological Research 49, 437-480, 2013 | 64 | 2013 |
| A framework and a mean-field algorithm for the local control of spatial processes R Sabbadin, N Peyrard, N Forsell International Journal of Approximate Reasoning 53 (1), 66-86, 2012 | 47 | 2012 |
| Quantifying the impact of uncertainty on threat management for biodiversity S Nicol, J Brazill-Boast, E Gorrod, A McSorley, N Peyrard, I Chadès Nature Communications 10 (1), 3570, 2019 | 44 | 2019 |
| Classification method for disease risk mapping based on discrete hidden Markov random fields M Charras-Garrido, D Abrial, JD Goër, S Dachian, N Peyrard Biostatistics 13 (2), 241-255, 2012 | 44 | 2012 |
| Motion-based selection of relevant video segments for video summarization N Peyrard, P Bouthemy Multimedia Tools and Applications 26, 259-276, 2005 | 43 | 2005 |
| Dynamics of weeds in the soil seed bank: a hidden Markov model to estimate life history traits from standing plant time series B Borgy, X Reboud, N Peyrard, R Sabbadin, S Gaba PloS one 10 (10), e0139278, 2015 | 41 | 2015 |
| The value of understanding feedbacks from ecosystem functions to species for managing ecosystems H Xiao, E McDonald-Madden, R Sabbadin, N Peyrard, LE Dee, I Chadès Nature Communications 10 (1), 3901, 2019 | 36 | 2019 |
| Win‐wins for biodiversity and ecosystem service conservation depend on the trophic levels of the species providing services H Xiao, LE Dee, I Chadès, N Peyrard, R Sabbadin, M Stringer, ... Journal of Applied Ecology 55 (5), 2160-2170, 2018 | 36 | 2018 |
| Mean field approximation of the policy iteration algorithm for graph-based Markov decision processes N Peyrard, R Sabbadin Frontiers in Artificial Intelligence and Applications 141, 595, 2006 | 30 | 2006 |
| Model-based adaptive spatial sampling for occurrence map construction N Peyrard, R Sabbadin, D Spring, B Brook, R Mac Nally Statistics and Computing 23, 29-42, 2013 | 28 | 2013 |
| Explorer un jeu de données sur grille par tests de permutation N Peyrard, A Calonnec, F Bonnot, J Chadoeuf Revue de Statistique Appliquée 53 (1), 59-78, 2005 | 28 | 2005 |
| Model-based region-of-interest selection in dynamic breast MRI F Forbes, N Peyrard, C Fraley, D Georgian-Smith, DM Goldhaber, ... Journal of Computer Assisted Tomography 30 (4), 675-687, 2006 | 23 | 2006 |
| Optimal spatial allocation of control effort to manage invasives in the face of imperfect detection and misclassification M Bonneau, J Martin, N Peyrard, L Rodgers, CM Romagosa, FA Johnson Ecological Modelling 392, 108-116, 2019 | 22 | 2019 |
| A general method for estimating seed dormancy and colonisation in annual plants from the observation of existing flora M Pluntz, SL Coz, N Peyrard, R Pradel, R Choquet, PO Cheptou Ecology letters 21 (9), 1311-1318, 2018 | 22 | 2018 |
| Approximations de type champ moyen des modèles de champ de Markov pour la segmentation de données spatiales N Peyrard Université Joseph Fourier (Grenoble), 2001 | 22 | 2001 |
| Reinforcement learning-based design of sampling policies under cost constraints in Markov random fields: Application to weed map reconstruction M Bonneau, S Gaba, N Peyrard, R Sabbadin Computational Statistics & Data Analysis 72, 30-44, 2014 | 21 | 2014 |
Régis SabbadinResearch Scientist, in Computer Science, INRAE, FranceVerifisert e-postadresse på inrae.fr