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Jean-Baptiste Durand

Jean-Baptiste Durand - Statistics and stochastic modelling of plant growth
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### Webpage: [http://amap-collaboratif.cirad.fr/pages-chercheurs/?page\_id=32153](http://amap-collaboratif.cirad.fr/pages-chercheurs/?page_id=32153) ### Short biography / Research topics Jean-Baptiste Durand received the engineering degree in applied mathematics and computer science from the "Institut National Polytechnique de Grenoble" [Grenoble INP](http://www.grenoble-inp.fr/grenoble-institute-of-technology-9224.kjsp?RH=INPG) (Grenoble Institute of Technology) in 1999. He received the Ph.D. degree in applied mathematics in 2003 from the University of Grenoble I (France), now [Université Grenoble Alpes](https://www.univ-grenoble-alpes.fr). From 1999 to 2003, he worked on statistical modelling at the French National Institute for Research in Computer Science and Control ([Inria](http://www.inria.fr/en/)), as a member of the [IS2 project](http://www.inrialpes.fr/is2) (Statistical Inference for Health and Industry). Then, he was a Postdoctoral Research Fellow at [AMAP](http://amap.cirad.fr/) "Plant Modelling" mixed research unit, Montpellier (France), with a grant from [CIRAD](http://www.cirad.fr/en). From 2004 to 2022, he was a teaching assistant at [Grenoble INP](http://www.grenoble-inp.fr/92723626/1/fiche___pagelibre/), member of the [Statify](https://team.inria.fr/statify/) team of [Laboratoire Jean Kuntzmann](http://www-ljk.imag.fr/). He was the head of the statistics and data science tracks of the international Master's programme MSIAM <http://msiam.imag.fr/>. He taught the fundamentals of statistics and computational statistics at the "École Nationale Supérieure d'Informatique et de Mathématiques Appliquées de Grenoble" [Ensimag](http://ensimag.grenoble-inp.fr/ecole-nationale-superieure-d-informatique-et-de-mathematiques-appliquees-74488.kjsp?RH=ENSIMAG_FR) (engineering school of applied mathematics and computer science). He was delegated to Inria team [Virtual Plants](http://team.inria.fr/virtualplants/) (Inria Sophia) between September 2009 and August 2011 and to Inria team [Statify](https://team.inria.fr/statify/) between September 2019 and August 2021 . His research interests include computational methods for hidden Markov models, statistical analysis of tree-structured processes, discrete multivariate distributions and applications to signal processing and botany. He has returned to [AMAP](http://amap.cirad.fr/) as a [CIRAD](http://www.cirad.fr/en) researcher since 2022 and now aims at developing statistical models and approaches for the analysis of structured data issued from plant phenotyping. ![](http://amap-collaboratif.cirad.fr/pages-chercheurs/wp-content/uploads/JDURAND_rain_lin.gif) ### Related working groups, research teams and pages - Research teams: - formerly [Virtual Plants](http://team.inria.fr/virtualplants/) (Inria Sophia), now [MOSAIC](https://www.inria.fr/fr/mosaic) in Lyon, see also their [research program](http://www.ens-lyon.fr/RDP/spip.php?rubrique52). - CIRAD [PhenoMEn](https://umr-agap.cirad.fr/nos-recherches/equipes-scientifiques/phenotypage-et-modelisation-des-plantes-dans-leur-environnement-agro-climatique/organisation-de-l-equipe) - mainly, the former M2P2 team (Montpellier) - AGAP [AFEF](https://umr-agap.cirad.fr/nos-recherches/equipes-scientifiques/architecture-et-floraison-des-especes-fruitieres/contexte-et-enjeux) (Montpellier) ![](http://amap-collaboratif.cirad.fr/pages-chercheurs/wp-content/uploads/JDURAND_rain_lin.gif) ### <a name="publis"></a>Publications (See [copyryight notice](http://amap-collaboratif.cirad.fr/pages-chercheurs/?page_id=32360)) #### [Publications on HAL](https://hal.archives-ouvertes.fr/search/index/q/*/authIdHal_s/jean-baptiste-durand) #### PhD thesis (defended the 31st of january 2003) ### Modèles à structure cachée : inférence, estimation, sélection de modèles et applications (in French) ([Compressed PDF](http://amap-collaboratif.cirad.fr/pages-chercheurs/wp-content/uploads/JDURAND_these.pdf.gz)) #### [Habilitation](https://en.wikipedia.org/wiki/Habilitation) thesis (defended the 19th of October 2020) ### Contributions to hidden Markov models and applications to plant structure analysis ([Compressed PDF](http://amap-collaboratif.cirad.fr/pages-chercheurs/wp-content/uploads/JDURAND_habilitation.pdf.gz)) #### Book - [Data Science. Cours et exercices.](https://www.eyrolles.com/Informatique/Livre/data-science-9782212674101) M.-R. Amini, R. Blanch, M. Clausel, J.-B. Durand, E. Gaussier, J. Malick, C. Picard, V. Quéma et G. Quénot. Eyrolles (Éd.), 2018. ![](http://amap-collaboratif.cirad.fr/pages-chercheurs/wp-content/uploads/JDURAND_rain_lin.gif) ### <a name="logiciels"></a>Software [OpenAlea](https://github.com/openalea/) - Author of package [TREE\_STATISTIC](https://github.com/openalea/StructureAnalysis/tree/master/tree_statistic) in [StructureAnalysis](https://github.com/openalea/StructureAnalysis) <!-- ### <a name="phd"></a>PhD Proposal #### Computational methods for hidden semi-Markov models with mixed effects -- application to plant and root branching patterns Profile and required skills required: Skills in statistics (modelling, parametric estimation) and if possible, random processes. Taste for applications and programming. ##### Abstract In the framework of plant development modelling, statistical models can be divided into two categories. The first one, referred to as "genotype x environment", is based on mixed models, which do not account for time dependencies existing in the considered processes. The second category is based on sequence analysis models that are funded on biological models, but currently do not account for genotype or environmental effects. More specifically, we are here focused on hidden semi-Markov models, introduced about 20 years ago (Guédon *et al.*, 2001) to model dynamical aspect of plant structure development. These models allow modellers to account for different development phases of either plants or their components (branches, roots, etc) through hidden states. The PhD proposal aims at including fixed and random effects within this category of models, the former aiming at characterising the effects of targeted covariates (genotype and environment) ant the latter, to account for constraints related to experimental design. The work to be accomplished, beyond model specification, is to develop inference algorithms suited to the specific complexity of these models . This PhD proposal opens avenues in two fields. Firstly, the newly developed family of models will be included as basic components within more global models, which is a major concern in model agronomic methods. Moreover, the methodological advances obtained in the hidden semi-Markov framework will enrich this family of models and offer new possibilities for addressing scientific questions in various domains of application (health, seismology, reliability, ecology, etc). ##### Context and aims The fast development of automatic platforms for plant phenotypic, achieving dynamical measurements of plant characteristics, is now leading to time and spatially dependent data. These data can lead to precious information to guide crop management, provided adequate models are built to analyse them. Most common plant development models are, one the one hand, deterministic approaches based on complex biological models, which hardly account for the observed phenotypic variability. On the other hand, statistical regression models offer possibilities to test genotype and environment effects, but they rely on over-simplistic biological time processes, for example summarized through an unique coefficient. Between both approaches, statistical methods including dynamical aspects of plant development were proposed by Guédon *et al.* (2001), in the framework of hidden Markov or semi-Markov models. These are based on plant representations motivated by biological knowledge (Barthélémy and Caraglio, 2007) and include a hidden variable, which represents plant development phases. However, such models do not account for genotypic and climatic effects.. This PhD proposal consists in extending the work by Guédon *et al.* (2001) by introducing fixed and random effects in the different distribution that define hidden semi-Markov models. Then, the aim is to propose inference algorithm with adequate accounting for model complexity. The latter is due to two levels of latent variables: hidden states corresponding to development phases ( categorical variables) and latent variables associated with random effects (continuous variables). ##### Methods and expected results Several methods are considered for inference. The first one relies on quadrature methods, whose specification and validity require a detailed study of the functions to be integrated, as in INLA (Rue *et al.*, 2009). The second one is Monte-Carlo approximation. The third one consists in Variational EM approximations (Jordan *et al.*, 1999, with VBEM as a variant in Bayesian analysis), based on an approximation of the log-likelihood with parametric functions being factorised with respect to some random variables. The work to be achieved includes a comparison of these methods regarding their abilities to accurately estimate parameters and to achieve the best possible compromise between accuracy and computation time. The issue of model selection wit usual criteria will have to be addressed, so as to determine which relevant covariates deserve to be part of the model. The selected methods for model inference will be applied on one or several available data sets in cereal root architecture, issued from research projects by Bertrand Muller [LEPSE](https://www6.montpellier.inrae.fr/lepse). Other potential applications are in fruit trees, with data issued from various agronomic contexts and projects from the [AFEF team](https://umr-agap.cirad.fr/nos-recherches/equipes-scientifiques/architecture-et-floraison-des-especes-fruitieres/liste-des-agents) (AGAP laboratory, INRAE). ##### Supervision The PhD will be co-supervised by Jean-Baptiste Durand (computational statistics), [AMAP](https://amap.cirad.fr/) Laboratory, CIRAD, and Bertrand Muller (ecophysiology), [LEPSE](https://www6.montpellier.inrae.fr/lepse). Nathalie Peyrard (computational statistics) at [MIAT research](https://miat.inra.fr/site/SCIDYN(english)) unit by INRAE Toulouse, Sandra Plancade (statistics and modelling) at MIAT and Evelyne Costes (genetics, botany and biostatistics) at AFEF team (AGAP laboratory, INRAE, Montpellier) will also take part to supervision. ##### Location and funding The PhD will take place at AMAP Laboratory, Cirad, in Montpellier (Agropolis district) https://amap.cirad.fr/. Visits to MIAT, INRAE Toulouse, will be planned: https://miat.inrae.fr/ Moreover, co-supervisers belong to [INCA](https://groupes.renater.fr/wiki/hsmm-inca/public/index) consortium (headed by N. Peyrard), which gathers most statisticians working on hidden semi-Markov models (both from theoretical and applied aspects) in France. Close collaborations, through regular working groups, will offer opportunities to interact with the community in statistics. Applicants are requested to join their full grade transcripts in third year of Bachelor, first year of Master and first semester, second year of Master (and even second semester if available), together with a resume and motivation letter. ##### Valorisation objectives The obtained results will lead to publications in computational statistics journals, in agronomy journals, and in journals in mathematical modelling for biology. The developed algorithm will be included in software packages for the statistical community in hidden semi-Markov models and adapted to the community in plant structure modelling. The PhD student will have the possibity to present his or her work in national and international workshops. ##### International collaborations The application to fruit specices (apple tree) is part of a collaboration with Martin Mészáros (Research and Breeding Institute of Pomology in Holovousy - VŠÚO - Czech Republic). An international workshop on Markovian and semi-Markovian models will be co-organised by INCA consortium in 2024. This will be an opportunity to meet international researchers with related topics and may lead to new collaborations. ##### References * Barthélémy, D. and Caraglio, Y. Plant Architecture : A Dynamic, Multilevel and Comprehensive Approach to Plant Form, Structure and Ontogeny. *Annals of Botany* **99**(3), 375–407 (2007) * Guédon, Y., Barthélémy, D., Caraglio, Y. and Costes, E. Pattern Analysis in Branching and Axillary Flowering Sequences. *Journal of theoretical biology*, **212**(4), 481–520 (2001) * Jordan, M.I., Ghahramani, Z., Jaakkola, T.S., Saul, L.K. An Introduction to Variational Methods for Graphical Models. *Machine Learning* **37**, 183–233 (1999) * Rue, H., Martino, S. and Chopin, N., Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations. *Journal of the Royal Statistical Society: Series B (Statistical Methodology*), **71**: 319-392 (2009) * Yu, S.-Z. Hidden semi-Markov models. *Artificial intelligence*, **174(2)**, 215–243 (2010) -->

Publications

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Hidden Semi-Markov Models to Segment Reading Phases from Eye Movements

Brice Olivier , Anne Guérin-Dugué , Jean-Baptiste Durand
Journal of Eye Movement Research, 2022, 15 (4), pp.5. ⟨10.16910/jemr.15.4.5⟩
Journal articles hal-03155843v2
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Bayesian nonparametric spatial prior for traffic crash risk mapping: a case study of Victoria, Australia

Jean-Baptiste Durand , Florence Forbes , Cong Duc Phan , Long Truong , Hien D Nguyen
Australian and New Zealand Journal of Statistics, 2022, Special Issue: Geoff McLachlan Festschrift, 64 (2), pp.171-204. ⟨10.1111/anzs.12369⟩
Journal articles hal-03138803v2
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Splitting models for multivariate count data

Jean Peyhardi , Pierre Fernique , Jean-Baptiste Durand
Journal of Multivariate Analysis, 2021, 181, pp.104677. ⟨10.1016/j.jmva.2020.104677⟩
Journal articles hal-02962877v1
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Comprendre un processus cognitif grâce à l’analyse statistique du mouvement des yeux

Jean-Baptiste Durand , Sophie Achard
Interstices, 2021
Journal articles hal-03505113v1
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Ornamental plants architectural characteristics in relation to visual sensory attributes: a new approach on the rose bush for objective evaluation of the visual quality

Morgan Garbez , Ronan Symoneaux , Etienne Belin , Yves Caraglio , Yann Chéné
European Journal of Horticultural Science, 2018, 83 (3), pp.187-201. ⟨10.17660/eJHS.2018/83.3.8⟩
Journal articles hal-01831318v1
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Predicting Flowering Behavior and Exploring Its Genetic Determinism in an Apple Multi-family Population Based on Statistical Indices and Simplified Phenotyping

Jean-Baptiste Durand , Alix Allard , Baptiste Guitton , Eric van de Weg , Marco Bink
Frontiers in Plant Science, 2017, 8, pp.858--872. ⟨10.3389/fpls.2017.00858⟩
Journal articles hal-01564977v1
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The impact of long-term water stress on tree architecture and production is related to changes in transitions between vegetative and reproductive growth in the ‘Granny Smith’ apple cultivar

Weiwei Yang , Benoit Pallas , Jean-Baptiste Durand , Sébastien S. Martinez , Mingyu Han
Tree Physiology, 2016, 36 (11), pp.1369-1381. ⟨10.1093/treephys/tpw068⟩
Journal articles hal-01377095v1
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Data Science : une formation internationale de niveau Master en science des données

Massih-Reza Amini , Jean-Baptiste Durand , Olivier Gaudoin , Eric Gaussier , Anatoli B. Juditsky
Statistique et Enseignement, 2016, 7 (1), pp.95-102
Journal articles hal-01342469v1
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Localizing the latent structure canonical uncertainty: entropy profiles for hidden Markov models

Jean-Baptiste Durand , Yann Guédon
Statistics and Computing, 2016, 26 (1), pp.549-567. ⟨10.1007/s11222-014-9494-9⟩
Journal articles hal-01090836v1
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New insights for estimating the genetic value of F1 apple progenies for irregular bearing during the first years of tree production

Jean-Baptiste Durand , Baptiste Guitton , Jean Peyhardi , Yan Holtz , Yann Guédon
Journal of Experimental Botany, 2013, 64 (16), pp.5099-5113. ⟨10.1093/jxb/ert297⟩
Journal articles hal-00845353v1
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Optimization of power consumption and user impact based on point process modeling of the request sequence

Jean-Baptiste Durand , Stéphane Girard , Victor Ciriza , Laurent Donini
Journal of the Royal Statistical Society: Series C Applied Statistics, 2013, 62 (2), pp.151-165. ⟨10.1111/j.1467-9876.2012.01053.x⟩
Journal articles hal-00412509v4
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Characteristics of Acacia mangium shoot apical meristems in natural and in vitro conditions in relation to heteroblasty

Clémence Hatt , François Mankessi , Jean-Baptiste Durand , Frédéric Boudon , Fabienne Montes
Trees - Structure and Function, 2012, 26 (3), pp.1031-1044. ⟨10.1007/s00468-012-0680-0⟩
Journal articles hal-00699815v1
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Selecting Hidden Markov Model State Number with Cross-Validated Likelihood

Gilles Celeux , Jean-Baptiste Durand
Computational Statistics, 2008, 23 (4), pp.541-564. ⟨10.1007/s00180-007-0097-1⟩
Journal articles inria-00193098v1

Analysis of the plant architecture via tree-structured statistical models: The hidden Markov tree models

Jean-Baptiste Durand , Yann Guédon , Yves Caraglio , Evelyne Costes
New Phytologist, 2005, 166 (3), pp.813-825. ⟨10.1111/j.1469-8137.2005.01405.x⟩
Journal articles hal-00017402v1
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Computational methods for hidden Markov tree models - An application to wavelet trees.

Jean-Baptiste Durand , Paulo Goncalvès , Yann Guédon
IEEE Transactions on Signal Processing, 2004, 52 (9), pp.2551-2560. ⟨10.1109/TSP.2004.832006⟩
Journal articles hal-00830078v1
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Analysing the architecture of Corylus avellana and parametrizing L-HAZELNUT FSPM

Francesca Grisafi , Sergio Tombesi , Daniela Farinelli , Frédéric Boudon , Jean-Baptiste Durand
FSPM 2023 - 10th International Conference on Functional-Structural Plant Models, Dr. Susann Müller, Mar 2023, Berlin, Germany. pp.1-2
Conference papers hal-04142608v1
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Semantic segmentation of sparse irregular point clouds for leaf/wood discrimination

Yuchen Bai , Jean-Baptiste Durand , Grégoire Vincent , Florence Forbes
NeurIPS 2023 - 37th Conference on Neural Information Processing Systems, Dec 2023, New-Orleans, United States. pp.1-21
Conference papers hal-04380350v1
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Architecture and yield relationship in hazelnut tree

Francesca Grisafi , Daniela Farinelli , Evelyne Costes , Frédéric Boudon , Jean-Baptiste Durand
XXXI International Horticultural Congress (IHC2022): International Symposium on Innovative Perennial Crops Management, Aug 2022, Angers, France. pp.331-336, ⟨10.17660/ActaHortic.2023.1366.40⟩
Conference papers hal-04137945v2
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Compétitions d’analyse des données à l’Université Grenoble Alpes : motivations, organisation et retours d’expérience

Jean-Baptiste Durand
CFIES 2019 - Colloque francophone international sur l'enseignement de la statistique, Sep 2019, Strasbourg, France. pp.1-6
Conference papers hal-02298606v1
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Approximation of trees by self-nested trees

Romain Azaïs , Jean-Baptiste Durand , Christophe Godin
ALENEX 2019 - Algorithm Engineering and Experiments, Jan 2019, San Diego, United States. pp.39-53, ⟨10.1137/1.9781611975499.4⟩
Conference papers hal-01294013v3
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Assessment of various initialization strategies for the Expectation-Maximization algorithm for Hidden Semi-Markov Models with multiple categorical sequences

Brice Olivier , Anne Guérin-Dugué , Jean-Baptiste Durand
JdS 2019 - 51èmes Journées de Statistique, Jun 2019, Vandœuvre-lès-Nancy, France. pp.1-7
Conference papers hal-02129122v1

Eye-tracking data analysis using hidden semi-Markovian models to identify and characterize reading strategies

Brice Olivier , Jean-Baptiste Durand , Anne Guérin-Dugué , Marianne Clausel
ECM 2017 - 19th European Conference on Eye Movements, Aug 2017, Wuppertal, Germany
Conference papers hal-01671224v1
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Genetic determinism of flowering regularity over years in an apple multi-family population

Jean-Baptiste Durand , Alix Allard , Baptiste Guitton , Eric van de Weg , Marco C. A. M. Bink
International Symposium on Flowering, Fruit Set and Alternate Bearing, Jun 2017, Palermo, Italy. pp.15-22, ⟨10.17660/ActaHortic.2018.1229.3⟩
Conference papers hal-01565681v1
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Challenges d'analyse de données : une formation par la pratique transversale et multidisciplinaire en science des données

Jean-Baptiste Durand
CFIES2017 - Colloque Francophone International sur l’Enseignement de la Statistique, Sep 2017, Grenoble, France
Conference papers hal-01611032v1

Impact of Long Term Water Deficit on Production and Flowering Occurrence in the 'Granny Smith' Apple Tree Cultivar

Benoit Pallas , Weiwei Yang , Jean-Baptiste Durand , Sébastien S. Martinez , Evelyne E. Costes
XI International Symposium on Integrating Canopy, Rootstock and Environmental Physiology in Orchard Systems, Prof. Dr. Luca Corelli-Grappadelli, Department of Agricultural Sciences, Università di Bologna, Aug 2016, Bologna, Italy
Conference papers hal-01377104v1
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Characterization of mango tree patchiness using a tree-segmentation/clustering approach

Pierre Fernique , Anaëlle Dambreville , Jean-Baptiste Durand , Christophe Pradal , Pierre-Eric P.-E. Lauri
2016 IEEE International Conference on Functional-Structural Plant Growth Modeling, Simulation, Visualization and Applications (FSPMA 2016), Nov 2016, Qingdao, China. pp.68-74, ⟨10.1109/FSPMA.2016.7818290⟩
Conference papers hal-01398291v1
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Analysis of the Impact of Carbon Source-sink Relationships on Flowering Patterns Reveals That Apple Tree Growth and Functioning are Determined by Mechanisms Occurring at the Tree and Shoot Scales

Benoit Pallas , Jérome Ngao , Jean-Baptiste Durand , Sébastien Martinez , Sylvie Bluy
XI International Symposium on Integrating Canopy, Rootstock and Environmental Physiology in Orchard Systems, L. Corelli Grappadelli, Aug 2016, Bologne, Italy. pp.405-412, ⟨10.17660/ActaHortic.2018.1228.60⟩
Conference papers hal-04182484v1
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Impact of long term water deficit on production and flowering occurrence in the ‘Granny Smith’ apple tree cultivar

Benoit Pallas , Weiwei Yang , Jean-Baptiste Durand , Sébastien S. Martinez , Evelyne E. Costes
11. Symposium on Integrating Canopy, Rootstockand Environmental Physiology in Orchard Systems, Aug 2016, Bologna, Italy
Conference papers hal-02741813v1
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Analyse de séquences oculométriques et d'électroencéphalogrammes par modèles markoviens cachés

Jean-Baptiste Durand , Anne Guérin-Dugué , Sophie Achard
JdS 2016 - 48èmes Journées de la Statistique, May 2016, Montpellier, France
Conference papers hal-01339458v1
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Détection de motifs disruptifs au sein de plantes : une approche de quotientement/classification d'arborescences

Pierre Fernique , Jean-Baptiste Durand , Yann Guédon
47èmes Journées de Statistique, Société Française de Statistique, Jun 2015, Lille, France
Conference papers hal-01240305v1
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Quantifying and localizing state uncertainty in hidden Markov models using conditional entropy profiles

Jean-Baptiste Durand , Yann Guédon
COMPSTAT 2014 - 21st International Conference on Computational Statistics, The International Association for Statistical Computing (IASC), Aug 2014, Genève, Switzerland. pp.213-221
Conference papers hal-01058278v1
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Quantification de l'incertitude sur la structure latente dans des modèles de Markov cachés

Jean-Baptiste Durand , Yann Guédon
46èmes Journées de Statistique, Société Française de Statistique (SFdS). FRA., Jun 2014, Rennes, France
Conference papers hal-01058317v1
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Estimation of Discrete Partially Directed Acyclic Graphical Models in Multitype Branching Processes

Pierre Fernique , Jean-Baptiste Durand , Yann Guédon
COMPSTAT 2014, 21st International Conference on Computational Statistics, The International Association for Statistical Computing (IASC), Aug 2014, Geneva, Switzerland. pp.561-568
Conference papers hal-01084524v1
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Modèles graphiques paramétriques pour la modélisation des lois de génération dans des processus de branchement multitypes

Pierre Fernique , Jean-Baptiste Durand , Yann Guédon
46èmes Journées de Statistique, Jun 2014, Rennes, France. 6 p
Conference papers hal-01058313v1

Approche graphique pour la modélisation statistique de la dépendance entre activités journalières

Jean-Baptiste Durand , Pierre Fernique
Workshop "Statistique, Transport et Activités", Nov 2013, Grenoble, France
Conference papers hal-00919372v1
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Deciphering mango tree asynchronisms using Markov tree and probabilistic graphical models

Anaëlle Dambreville , Pierre Fernique , Christophe Pradal , Pierre-Eric Lauri , Frédéric Normand
FSPM2013 - 7th International Workshop on Functional-Structural Plant Models, Jun 2013, Saariselkä, Finland. pp.210-212
Conference papers hal-00847614v1
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Estimating the genetic value of F1 apple progenies for irregular bearing during first years of production

Jean-Baptiste Durand , Baptiste Guitton , Jean Peyhardi , Yan Holtz , Yann Guédon
FSPM2013 - 7th International Workshop on Functional-Structural Plant Models, Jun 2013, Saariselkä, Finland. pp.13-15
Conference papers hal-00847593v1
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Parametric Modelling of Multivariate Count Data Using Probabilistic Graphical Models

Pierre Fernique , Jean-Baptiste Durand , Yann Guédon
AIGM13 - 3rd Workshop on Algorithmic issues for Inference in Graphical Models, Sep 2013, Paris, France
Conference papers hal-00918597v1
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Reconstructing Plant Architecture from 3D Laser scanner data

Chakkrit Preuksakarn , Frédéric Boudon , Pascal Ferraro , Jean-Baptiste Durand , Ekko Nikinmaa
6th International Workshop on Functional-Structural Plant Models, Sep 2010, Davis, United States. pp.12--17
Conference papers hal-00490064v1

A statistical model for optimizing power consumption of printers

Victor Ciriza , Laurent Donini , Jean-Baptiste Durand , Stéphane Girard
XIG R & T Conference, Xerox Corporation, May 2008, Webster, United States
Conference papers hal-00847605v1

A Statistical Model for Optimizing Power Consumption of Printers

Victor Ciriza , Laurent Donini , Jean-Baptiste Durand , Stéphane Girard
40èmes Journées de Statistique, Congrès conjoint de la Société Statistique du Canada et de la Société Française de Statistique, May 2008, Ottawa, Canada. pp.227
Conference papers inria-00320053v1
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Segmentation-based approaches for characterising plant architecture and assessing its plasticity at different scales

Jean-Baptiste Durand , Yves Caraglio , Patrick Heuret , Eric Nicolini
FSPM07 - 5th International Workshop on Functional-Structural Plant Models, Nov 2007, Napier, New Zealand. pp.39:1-3
Conference papers hal-00831827v1
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Calcul de probabilités et estimation dans des modèles de Markov cachés graphiques

Jean-Baptiste Durand
39èmes Journées de Statistique, Société Française de Statistique, Jun 2007, Angers, France
Conference papers inria-00179396v1

Exploring morphogenetical gradients plasticity using hidden Markov tree models in young individuals of the tropical specie Symphonia globulifera (Clusiaceae)

Patrick Heuret , Jean-Baptiste Durand , Éric Nicolini , Sabrina Coste , Yves Caraglio
FSPM07 - 5th International Workshop on Functional-Structural Plant Models, Nov 2007, Napier, New Zealand. pp.P19:1-1
Conference papers hal-00847590v1
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OpenAlea: An open-source platform for the integration of heterogeneous FSPM components

Samuel Dufour-Kowalski , Christophe Pradal , Nicolas Dones , Pierre Barbier de Reuille , Frédéric Boudon
FSPM07 - 5th International Workshop on Functional-Structural Plant Models, Nov 2007, Napier, New Zealand. pp.P36:1-2
Conference papers hal-00831824v1

OpenAlea : a platform for plant modelling, analysis and simulation

Christophe Pradal , Frédéric Boudon , Nicolas Dones , Jean-Baptiste Durand , Pierre Barbier de Reuille
Python Conference Europython, 2006, Genève, Switzerland. 16 p
Conference papers hal-01189325v1

Arbres de Markov cachés : inférence et applications

Jean-Baptiste Durand , Paulo Gonçalves , Yann Guédon
Proceedings of XXXVI èmes Journées de Statistique, May 2004, Montpellier, France
Conference papers inria-00570624v1

Analysis of the plant architecture via tree-structured statistical models: the hidden Markov tree models

Jean-Baptiste Durand , Yann Guédon , Yves Caraglio , Evelyne E. Costes
4th International workshop on functional-structural plant models (FSPM), Jun 2004, Montpellier, France. pp.813-825, ⟨10.1111/j.1469-8137.2005.01405.x⟩
Conference papers hal-02833214v1
Image document

Lossy compression of unordered rooted trees

Romain Azaïs , Jean-Baptiste Durand , Christophe Godin
DCC 2016 - Data Compression Conference, Mar 2016, Snowbird, Utah, United States. ⟨10.1109/DCC.2016.73⟩
Conference poster hal-01394707v1

Modèles génératifs

Marianne Clausel , Jean-Baptiste Durand
Data Science. Cours et exercices, Eyrolles, 2018, 978-2-212-67410-1
Book sections hal-01961722v1