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Modèles markoviens de ressources partagées

Florence Forbes
Modélisation et simulation. Université Joseph-Fourier - Grenoble I, 1996. Français. ⟨NNT : ⟩
Thèse tel-00004991v1
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A convergence theorem for variational EM-like algorithms: application to image segmentation

Florence Forbes , Gersende Fort
RR-5721, INRIA. 2005, pp.36
Rapport inria-00070297v1

Model-based region-of-interest selection in dynamic breast MRI

Florence Forbes , Nathalie Dubois Peyrard Peyrard , C. Fraley , Dianne Georgian-Smith , David M. Goldhaber , et al.
Journal of Computer Assisted Tomography, 2006, 30 (4), pp.675-687
Article dans une revue hal-02656483v1

Surrogate posteriors for Approximate Bayesian Computation

Florence Forbes
SIAM Conference on Computational Science and Engineering (CSE21), Likelihood-free inference minisymposium, Mar 2021, Virtual, France
Communication dans un congrès hal-03874042v1

Online Majorization Minimization algorithms

Florence Forbes
CIRM Workshop on Computational Methods for Unifying Multiple Statistical Analyses (Fusion), Oct 2022, Luminy, France
Communication dans un congrès hal-03874028v1
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Models and inference for structured stochastic systems

Florence Forbes
Modeling and Simulation. Université de Grenoble, 2010
HDR tel-00578938v1

Simulation-based Bayesian inference for high dimensional inverse problems

Florence Forbes
CIRM Research school on End-to-end Bayesian Learning Methods, Oct 2021, Luminy, France
Communication dans un congrès hal-03874016v1

Simulation-based approaches to Bayesian inverse problems

Florence Forbes
ICMS 2023 - Workshop on Interfacing Bayesian statistics, machine learning, applied analysis, and blind and semi-blind imaging inverse problems, Jan 2023, Edimburgh, United Kingdom
Communication dans un congrès hal-03874057v1

Simulation based inference for high dimensional inverse problems: application to magnetic resonance fingerprinting

Florence Forbes
Colloque  Intelligence Artificielle et santé : approches interdisciplinaires 2022, Jun 2022, Nantes, France
Communication dans un congrès hal-03876812v1

Learning approaches for Bayesian inverse problems

Florence Forbes
UGA-McMaster joint workshop 2022, Jun 2022, Hamilton, Canada
Communication dans un congrès hal-03874054v1
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Modelling structured data with probabilistic graphical models

Florence Forbes
D. Fraix-Burnet; S. Girard. Statistics for Astrophysics- Classification and Clustering, 77, EDP Sciences, pp.195-219, 2016, EAS Publication Series, ⟨10.1051/eas/1677009⟩
Chapitre d'ouvrage istex hal-01423613v1

Summary statistics and discrepancy measures for approximate Bayesian computation via surrogate posteriors

Florence Forbes
BayesComp 2023 - Conference of the Bayesian Computation Section of the International Society for Bayesian Analysis, Mar 2023, Levi, Finland
Communication dans un congrès hal-03874011v1

Student sliced inverse regression

Florence Forbes , Alessandro Chiancone , Stéphane Girard
9th International Conference of the ERCIM WG on Computational and Methodological Statistics, Dec 2016, Seville, Spain
Communication dans un congrès hal-01415576v1
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Bayesian Morphology: Fast Unsupervised Bayesian Image Analysis

Florence Forbes , Adrian E. Raftery
RR-3374, INRIA. 1998
Rapport inria-00073315v1
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Mixture Models for Image Analysis

Florence Forbes
Sylvia Fruhwirth-Schnatter; Gilles Celeux; Christian P. Robert. Handbook of Mixture Analysis, CRC press, pp.397-418, 2018, 9781498763813
Chapitre d'ouvrage hal-01970681v1
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Introduction to statistical methods in signal and image processing

Florence Forbes
Doctoral. Peyresq, France. 2016
Cours cel-01423624v1

Robust mixture modelling using skewed multivariate distributions with variable amounts of tailweight

Florence Forbes , Darren Wraith
JdS 2019 - 51èmes Journées de Statistique, Jun 2019, Nancy, France
Communication dans un congrès hal-02423639v1

Modèles markoviens pour l'organisation spatiale de descripteurs d'images

Juliette Blanchet , Florence Forbes , Cordelia Schmid
37e Journées de Statistique de la Société Française de Statistique, Jun 2005, Pau, France
Communication dans un congrès inria-00548519v1
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Global implicit function theorems and the online Expectation-Maximisation algorithm

Hien Duy Nguyen , Florence Forbes
Australian and New Zealand Journal of Statistics, 2022, 64 (2), pp.255-281. ⟨10.1111/anzs.12356⟩
Article dans une revue hal-03110213v2
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Location and scale mixtures of Gaussians with flexible tail behaviour: properties, inference and application to multivariate clustering

Darren Wraith , Florence Forbes
Computational Statistics and Data Analysis, 2015, 90, pp.61-73. ⟨10.1016/j.csda.2015.04.008⟩
Article dans une revue hal-01970565v1

Clustering of incomplete, high dimensional and dependent biological data with SpaCEM3

Matthieu Vignes , Juliette Blanchet , Damien Leroux , Florence Forbes
Journée Satellite JOBIM MODGRAPH 2010, Sep 2010, Montpellier, France
Communication dans un congrès hal-00780725v1

Student Sliced Inverse Regression

Florence Forbes , Alessandro Chiancone , Stéphane Girard
23th summer session of the Working Group on Model-based Clustering, Jul 2016, Paris, France
Communication dans un congrès hal-01423626v1

Automatic learning of functional summary statistics for approximate Bayesian computation

Florence Forbes
O'Bayes 2022 - Objective Bayes Methodology Conference, Sep 2022, Santa Cruz, United States
Communication dans un congrès hal-03874003v1
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A new family of multivariate heavy-tailed distributions with variable marginal amounts of tailweights: Application to robust clustering

Florence Forbes , Darren Wraith
Statistics and Computing, 2014, 24 (6), pp.971-984. ⟨10.1007/s11222-013-9414-4⟩
Article dans une revue hal-00823451v2

Triplet Markov fields for the classification of complex structure data

Juliette Blanchet , Florence Forbes
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2008, 30 (6), pp.1055-1067. ⟨10.1109/TPAMI.2008.27⟩
Article dans une revue hal-00846808v1
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Triplet Markov fields for the classification of complex structure data

Juliette Blanchet , Florence Forbes
[Research Report] RR-6356, INRIA. 2007
Rapport inria-00168621v2

Gene clustering via integrated Markov models combining individual and pairwise features.

Matthieu Vignes , Florence Forbes
IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2009, 6 (2), pp.260-270. ⟨10.1109/TCBB.2007.70248⟩
Article dans une revue hal-00781174v1

Modèles markoviens pour l'organisation spatiale de descripteurs d'images

Juliette Blanchet , Florence Forbes , Cordelia Schmid
Conférence Francophone sur l'Apprentissage Automatique (CAP '05), May 2005, Nice, France. pp.113-126
Communication dans un congrès inria-00548521v1

An improved CUDA-based implementation of differential evolution on GPU

Kai Qin , Federico Raimondo , Florence Forbes , Yew Soon Ong
GECCO '12 - 14th international conference on Genetic and evolutionary computation conference, Jul 2012, Philadelphia, United States. pp.991-998, ⟨10.1145/2330163.2330301⟩
Communication dans un congrès hal-00780081v1

Dynamic Regional Harmony Search with Opposition and Local Learning

A. Kai Qin , Florence Forbes
GECCO'11 - 13th annual conference companion on Genetic and evolutionary computation, Jul 2011, Dublin, Ireland. pp.53-54, ⟨10.1145/2001858.2001890⟩
Communication dans un congrès hal-00780548v1