G. Oudoumanessah, T. Coudert, C. Lartizien, M. Dojat, T. Christen, F. Forbes. Scalable magnetic resonance fingerprinting: Incremental inference of high dimensional elliptical mixtures from large data volumes, (pdf)

J. Iollo, C. Heinkele, P. Alliez, F. Forbes. Bayesian Experimental Design via Contrastive Diffusions, (pdf)

H. Donancio, A. Barrier, L. F. South, F. Forbes. Dynamic Learning Rate for Deep Reinforcement Learning: A Bandit Approach (pdf)

G. Fort, F. Forbes, H.D. Nguyen. Sequential Sample Average Majorization Minimization, (pdf)

H. D. Nguyen, T. T. Nguyen, J. Arbel, F. Forbes. Concentration results for approximate Bayesian computation without identifiability. Preprint and supplementary material (pdf)

TT Nguyen, F Chamroukhi, HD Nguyen, F Forbes. Non-asymptotic model selection in block-diagonal mixture of polynomial experts models. (pdf)

K. Ashurbekova, A. Usseglio-Carleve, F. Forbes, S. Achard. Optimal shrinkage for robust covariance matrix estimators in a small sample size setting. Working paper (pdf)

A. Arnaud, F. Forbes, R. Steele, B. Lemasson, E. Barbier. Bayesian mixtures of multiple scale distributions. Working paper (pdf)

T. Rahier, S. Marie , S. Girard, F. Forbes, Fast Bayesian Network Structure Learning using Quasi-determinism Screening, working paper (pdf)

T. Nguyen, F. Forbes, J. Arbel, H.D. Nguyen. Bayesian nonparametric mixture of experts for high-dimensional inverse problems, Journal of Nonparametric Statistics, (pdf)(eprint)

H. Haggstrom, P.L.C. Rodrigues, G. Oudoumanessah, F. Forbes, U. Picchini. Fast, accurate and lightweight sequential simulation-based inference using Gaussian locally linear mappings. Transactions on Machine Learning Research, (pdf)

B. Lambert, F. Forbes, S. Doyle, H. Dehaene, M. Dojat. Trustworthy clinical AI solutions: a unified review of uncertainty quantification in deep learning models for medical image analysis. Artificial Intelligence in Medicine, Volume 150, April 2024, (pdf)

B. Lambert, F. Forbes, S. Doyle, M.Dojat. Robust Conformal Volume Estimation in 3D Medical Images , In Proceedings of The 27th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2024, Early Acceptance rate 11% over 2869 submissions. (pdf)

J. Iollo, C. Heinkele, P. Alliez, F. Forbes. PASOA-PArticle baSed Bayesian Optimal Adaptive design, In Proceedings of The 41st International Conference on Machine Learning, ICML 2024, Acceptance rate 27.5% over 9,473 submissions. (pdf)

F. Forbes, H.D. Nguyen, T.T. Nguyen. Bayesian Likelihood Free Inference using Mixtures of Experts. In International Joint Conference on Neural Networks, IJCNN 2024. (pdf)

B. Marc, P. Foucher, F. Forbes, P. Charbonnier. Normalizing flows with task-specific pre-training for unsupervised anomaly detection on engineering structures, 32nd European Signal Processing Conference (EUSIPCO 2024), Lyon, August 2024. (pdf)

S. Doute, F. Forbes, S. Borkowski, L. Meyer, S. Heidmann. Massive analysis of multi-angular images by inverse regression of reflectance models for the physical characterization of planetary surfaces. Europlanet Science Congress 2024, Berlin, Germany, in MITM4--Imagery, photometry, and spectroscopy of small bodies and planetary surfaces. (link)

B. Marc, P. Foucher, F. Forbes, P. Charbonnier. Evaluation de methodes de detection d'anomalies non supervisee pour l'auscultation des ouvrages d'art. RFIAP 2024 - Congres Reconnaissance des Formes, Image, Apprentissage et Perception, AFRIF (Association Francaise pour la Reconnaissance et l'Interpretation des Formes), Jul 2024, Lille, France. (pdf)

Y. Bai, J.B. Durand, G. Vincent, F. Forbes. Semantic segmentation of forest point clouds using neural network, JDS2024, 55emes Journees de Statistique de la SFdS,(pdf)

C. Gain, B. Rhone, P. Cubry, I. Salazar, F. Forbes, Y. Vigouroux, F. Jay, O. Francois. A quantitative theory for genomic offset statistics, To appear in Molecular Biology and Evolution, 2023, (pdf)

Y. Bai, J.B. Durand, G. vincent, F. Forbes. Semantic Segmentation of sparse irregular point clouds for leaf/wood area estimation, NeurIPS 2023, New Orleans USA (pdf)

B. Lambert, F. Forbes, S. Doyle, M. Dojat. TriadNet: Sampling-free predictive intervals for lesional volume in 3D brain MRI, 5th International Workshop, UNSURE 2023, at MICCAI 2023 Vancouver, BC, Canada, (pdf)

B. Lambert, F. Forbes, S. Doyle, M. Dojat. Multi-layer Aggregation as a Key to Feature-Based OOD Detection, 5th International Workshop, UNSURE 2023, at MICCAI 2023 Vancouver, BC, Canada, (pdf)

B. Lambert, P. Roca, F. Forbes, S. Doyle, M. Dojat. Anisotropic Hybrid Networks for liver tumor segmentation with uncertainty quantification, MICCAI Workshop on 2nd Resource-Efficient Medical Image Analysis (REMIA) (pdf)

G. Oudoumanessah, C. Lartizien, M. Dojat, F. Forbes. Towards frugal unsupervised detection of subtle abnormalities in medical imaging, International Conference on Medical Image Computing and Computer Assisted Intervention MICCAI, Vancouver, Canada, October 2023, Acceptance rate 32% over 2,250 submissions. (pdf)

B. Lambert, F. Forbes, S. Doyle, A Tucholka, M. Dojat. Uncertainty-based Quality Control for Subcortical Structures Segmentation in T1-weighted Brain MRI,International Society for Magnetic Resonance in Medicine (ISMRM), Toronto, Canada, 2023, (pdf)

S Ancelet, C Damon, T Silvestre, A Bressand, M Dojat, B Lemasson, Alan Tucholka, Guillaume Jarre, Florence Forbes, Alain Trouvé, Nadya Pyatigorskaya, Lucia Nichelli, Monica Ribeiro, Julian Jacob, Philippe Meyer, Catherine Jenny, Caroline Dehais, Alexander Balcerac, Jean-Marie Mirebeau, Sophie Achard, Loic Feuvret, Dimitri Psimaras, Georges Noel, Philippe Maingon, Jean-Damien Ricard, Marie-Odile Bernier. Radiation-induced neurotoxicity assessed by spatio-temporal modelling combined with artificial Intelligence after brain radiotherapy: the RADIO-AIDE project, International Society for Radiation Epidemiology and Dosimetry 1st meeting (pdf)

N. Pinon, G. Oudoumanessah, R. Trombetta, M. Dojat, F. Forbes, C. Lartizien. Brain subtle anomaly detection based on Auto-Encoders latent space analysis: Application to de novo Parkinson patients, IEEE International Symposium on Biomedical Imaging (ISBI) 2023, Cartagena, Columbia, April 18 - 21, 2023, (pdf)

B. Lambert, F. Forbes, S. Doyle, A. Tucholka, M. Dojat. Uncertainty-based Quality Control for Subcortical Structures Segmentation in T1-weighted Brain MRI, International Society for Magnetic Resonance in Medicine (ISMRM) 2023, (pdf)

B. Lambert, F. Forbes, S. Doyle, A. Tucholka, M. Dojat. Intervalles de confiance pour l'estimation de superficies a partir d'images satellitaires, Colloque Francophone du Traitement du Signal et des Images, GRETSI, Grenoble, August 2023, (pdf)

J. Iollo, C. Heinkele, P. Alliez, F. Forbes. Tempered SMC for Sequential Bayesian Optimal Design, Colloque Francophone du Traitement du Signal et des Images, GRETSI, Grenoble, August 2023, (pdf)

S. Doute, F. Forbes, S. Borkowski, S. Heidmann, L. Meyer. Massive analysis of multidimensional astrophysical data by inverse regression of physical models, Colloque Francophone du Traitement du Signal et des Images, GRETSI, Grenoble, August 2023, (pdf)

G. Oudoumanessah, C. Lartizien, M. Dojat, F. Forbes. Estimation incrementale pour la detection non supervisee d'anomalies multivariees en imagerie medicale, Colloque Francophone du Traitement du Signal et des Images, GRETSI, Grenoble, August 2023, (pdf)

B. Lambert, F. Forbes, S. Doyle, A. Tucholka, M. Dojat. Safety-Net: Identification automatique des erreurs de segmentation des lesions de la Sclerose-en-Plaques, Societe Francaise de Resonance Magnetique en Biologie et Medecine, (pdf)

H. Nguyen, S. Lee, and F. Forbes. A Festschrift for Geoff McLachlan. Australian and New Zealand Journal of Statistics, 64 (2), 111-116. (pdf)

F. Forbes, H. D. Nguyen, T. T. Nguyen, J. Arbel . Summary statistics and discrepancy measures for approximate Bayesian computation via surrogate posteriors. Statistics and Computing,32,85, 2022. preprint and supplementary material (pdf)

TT Nguyen, HD Nguyen, F Chamroukhi, F Forbes. A non-asymptotic approach for model selection via penalization in high-dimensional mixture of experts models. Electronic Journal of Statistics,16,2,Sept 2022, p.4742-4822. (preprint)

J.-B. Durand, F. Forbes, C.D. Phan, L. Truong, H. Nguyen, F. Dama. Bayesian nonparametric spatial prior for traffic crash risk mapping: a case study of Victoria, Australia. Australian and New Zealand Journal of Statistics 64, 2, June 2022, p.171-204. (open access, preprint)

V. Munoz-Ramirez, V. Kmetzsch, F. Forbes, S. Meoni, E. Moro, M. Dojat. Subtle anomaly detection in MRI brain scans: Application to biomarkers extraction in patients with de novo Parkinson's disease. Artificial Intelligence in Medicine 125, March 2022, p.102251. (pdf)

H. D. Nguyen, F. Forbes. Global implicit function theorems and the online expectation-maximisation algorithm. Australian and New Zealand Journal of Statistics,64, 2, June 2022, p.255-281. (pdf)

T Mistral, P Roca, C Maggia, A Tucholka, F Forbes, S Doyle, A Krainik, et al. Automated quantification of brain lesion volume from post-trauma MR diffusion-weighted images. Frontiers in Neurology,12, Feb 2022, p.740603. (pdf)

T. Rahier, S. Marie , F. Forbes, A Pre-Screening Approach for Faster Bayesian Network Structure Learning, ECML-PKDD, September 19-23, 2022, Grenoble, (pdf)

B. Lambert, F. Forbes, S. Doyle, A. Tucholka, M. Dojat . Beyond Voxel Prediction Uncertainty: Identifying brain lesions you can trust. Workshop on Interpretability of Machine Intelligence in Medical Image Computing at MICCAI 2022, Singapore, Sept. 2022, (pdf)

H. D. Nguyen, F. Forbes, G. Fort, O. Cappe. An online Minorization-Maximization algorithm. 2022 International Federation of Classification Societies (IFCS) conference, Porto, Portugal, July 19-23. (pdf)

B. Lambert, F. Forbes, S. Doyle, A. Tucholka, M. Dojat. Multi-Scale Evaluation of Uncertainty Quantification Techniques for Deep Learning based MRI Segmentation. Joint Annual Meeting ISMRM-ESMRMB & ISMRT 31st Annual Meeting, 07-12 May 2022 in London, England, UK, (pdf)

B. Lambert, F. Forbes, S. Doyle, A. Tucholka, M. Dojat. Fast Uncertainty Quantification for Deep Learning-based MR Brain Segmentation. Conference francophone sur l'extraction et la gestion des connaissances, Jan 2022, Blois, France. (pdf)

TT Nguyen, F Chamroukhi, HD Nguyen, F Forbes. Model selection by penalization in mixture of experts models with a non-asymptotic approach. 53emes Journees de Statistique de la Societe Francaise de Statistique (SFdS), Jun 2022, Lyon, France. (pdf)

F. Forbes, H.D. Nguyen, T.T. Nguyen, J. Arbel. Mixture of expert posterior surrogates for approximate Bayesian computation. 53emes Journees de Statistique de la Societe Francaise de Statistique (SFdS), Jun 2022, Lyon, France. (pdf)

S.M. Potin, S. Doute, B. Kugler, F. Forbes. The impact of asteroid shapes and topographies on their reflectance spectroscopy. Icarus, Elsevier, 2021, pp.114806.(pdf)

B. Kugler, F. Forbes, S. Doute. Fast Bayesian Inversion for high dimensional inverse problems. Statistics and Computing 32, 31, March 2022. (pdf)

F. Boux, F. Forbes, J. Arbel, B. Lemasson, E. Barbier. Bayesian inverse regression for vascular magnetic resonance fingerprinting. IEEE Trans. on Medical Imaging 40, 7, July 2021, p. 1827-1837. (pre-print pdf)

F. Boux, F. Forbes, N. Collomb, E. Zub, L. Maziere, F. de Bock, M. Blaquiere, V. Stupar, A. Depaulis, N. Marchi and E. L. Barbier. Neurovascular multiparametric MRI defines epileptogenic and seizure propagation regions in experimental mesiotemporal lobe epilepsy. Epilepsia 62,5, May 2021, p. 1244-1255. (pdf)

V. Munoz-Ramirez, N. Pinon, F. Forbes, C. Lartizien, M. Dojat. Patch vs. Global Image-Based Unsupervised Anomaly Detection in MR Brain Scans of Early Parkinsonian Patients. 4th International Workshop in Machine Learning in Clinical Neuroimaging, MLCN 2021, held in Conjunction with MICCAI 2021, Sep 2021, Strasbourg, France. pp.34-43, (pdf)

SM Potin, S Doute, B Kugler, F Forbes. Comparison of photometric phase curves resulting from various observation scenes, Europlanet Science Congress (EPSC), Sept, 2021. (poster)

B. Lambert, M. Louis, S. Doyle, F. Forbes, M. Dojat, A. Tucholka. Leveraging 3D Information in Unsupervised Brain MRI Segmentation. ISBI 2021 - IEEE International Symposium on Biomedical Imaging, Apr 2021, Nice, France. (pdf)

SM Potin, S Doute, B Kugler, F Forbes. Simulated Observations of Small Bodies: The Effect of Shape and Topography. Lunar and Planetary Science Conference, held virtually, 15-19 March, 2021. LPI Contribution No. 2548, id.1542

B. Kugler, F. Forbes, S. Doute, M. Gay. Efficient Bayesian data assimilation via inverse regression JDS 2021 : 52emes Journees de Statistique de la Societe Francaise de Statistique, Jun 2021, Nice, France (pdf)

Hien D. Nguyen, Julyan Arbel, Hongliang Lu, and Florence Forbes. Approximate Bayesian computation via the energy statistic, IEEE Access, p.1-16. (pdf)

H. Lu, J. Arbel, F. Forbes, Bayesian nonparametric priors for hidden Markov random fields, Statistics and Computing 30, 2020, p. 1015-1035. (pdf)

B. Kugler, F. Forbes, S. Doute. An efficient Bayesian method for inverting physical models on massive planetary data. Accepted for oral presentation in SB11 - Physical properties of small bodies: observations and techniques, Europlanet Science Congress (EPSC), Sept. 21- Oct.9 2020. (pdf)

S. Potin, S. Doute, B. Kugler, F. Forbes, P. Beck, B. Schmitt. Simulated phase curves of Vesta based on laboratory bidirectional reflectance spectroscopy. Accepted for oral presentation in SB11 - Physical properties of small bodies: observations and techniques, Europlanet Science Congress (EPSC), Sept. 21- Oct.9 2020. (pdf)

F. Zheng, S. Bonnet, E. Villeneuve, M. Doron, A. Lepecq, F. Forbes. Unannounced Meal Detection for Artificial Pancreas Systems Using Extended Isolation Forest. 42nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Montreal, July 2020.(pdf)

V. Munoz Ramirez, V. Kmetzsch, F. Forbes, M. Dojat. Deep learning models to study the early stages of Parkinson's Disease. ISBI 2020 - IEEE International Symposium on Biomedical Imaging, Apr 2020, Iowa city, USA.(pdf)

F. Boux, F. Forbes, J. Arbel, A. Delphin, T. Christen and E. L. Barbier, Dictionary-based learning methods in MR Fingerprinting: Machine Learning versus Deep Learning. ISMRM, p. 1-4, August 2020, Sydney, Australia. (pdf)

H. Lu, F. Forbes, J. Arbel. Bayesian Nonparametric Priors for Graph Structured Data: Application to Image Segmentation, Bayes Comp 2020, Jan 2020, Gainesville, United States (poster)

B. Kugler, F. Forbes, S. Doute. First order Sobol indices for physical models via inverse regression. 52emes Journees de Statistiques de la Societe Francaise de Statistique (SFdS), Nice 2020 postponed to 2021, (pdf)

Hien D. Nguyen, Florence Forbes and Geoffrey J. McLachlan. Mini-batch learning of exponential family finite mixture models, Statistics and Computing 30,July 2020, p. 731-748. (pdf)

Fei Zheng, Manon Jalbert, Florence Forbes, Stephane Bonnet, Anne Wojtusciszyn, Sandrine Lablanche, Pierre-Yves Benhamou. Characterization of Daily Glycemic Variability in Subjects with Type 1 Diabetes with mixture of metrics . Diabetes Technology and Therapeutics 22,4, April 2020, p. 301-313. (pdf)

Manon Jalbert, Fei Zheng, Anne Wojtusciszyn, Florence Forbes, Stephane Bonnet, Kristina Skaare, Pierre-Yves Benhamou, Sandrine Lablanche. Glycemic variability indices can be used to diagnose islet transplantation success in type 1 diabetic patients. Acta Diabetologica, 57, Marc 2020, p. 335-345. (pdf)

Hien Nguyen, Faicel Chamroukhi, Florence Forbes. Approximation results regarding the multiple-output Gaussian gated mixture of linear experts model. Neurocomputing 366,Nov. 2019, p. 208-214. (pdf)

C.-C. Tu, F. Forbes, N. Wang, B. Lemasson, Prediction with high dimensional regression via hierarchically structured Gaussian mixtures and latent variables. Journal of the Royal Statistical Society: Series C Applied Statistics 68, 5, Nov. 2019, p. 1485-1507, (pdf)

K. Ashurbekova, S. Achard, F. Forbes. Structure learning via Hadamard product of correlation and partial correlation matrices. EUSIPCO 2019, (pdf)

K. Ashurbekova, S. Achard, F. Forbes. Robust penalized inference for Gaussian Scale Mixtures. SPARS 2019, Jul 2019, Toulouse, France, (pdf)

F. Forbes, A. Arnaud, B. Lemasson, E. Barbier (2019). Component Elimination Strategies to Fit Mixtures of Multiple Scale Distributions. In: Nguyen H. (eds) Statistics and Data Science. RSSDS 2019, July 2019, Melbourne, Australia. Communications in Computer and Information Science, vol 1150. Springer, Singapore, (slides), (pdf)

V. Munoz Ramirez, F. Forbes, J. Arbel, A. Arnaud, M. Dojat. Quantitative MRI characterization of brain abnormalities in de novo Parkinsonian patients ISBI 2019 - IEEE International Symposium on Biomedical Imaging, Apr 2019, Venice, Italy. pp.1-4. (pdf)

V. Munoz Ramirez, F. Forbes, P. Coupe, M. Dojat. No Structural Brain Differences in 'de novo' Parkinsonian Patients. OHBM 2019 (pdf)

V. Munoz Ramirez, F. Forbes, A. Arnaud, M. Dojat. Brain Abnormalities Detection in de novo Parkinsonian Patients, OHBM 2019 (pdf)

V. Munoz Ramirez, F. Forbes, P. Coupe, M. Dojat. No Structural Differences Are Revealed by VBM in 'de novo' Parkinsonian Patients, MEDINFO 2019 - 17th World Congress On Medical And Health Informatics, Aug 2019, Lyon, France. pp.268-272, (pdf)

F. Forbes, A. Deleforge, R. Horaud, E. Perthame, Robust non-linear regression approach for generalized inverse problems in a high dimensional setting, AIP 2019 Applied Inverse Problem conference, July 2019, Grenoble, France. (pdf)

B. Kugler, F. Forbes, S. Doute. Massive hyperspectral images analysis by inverse regression of physical models. StatLearn 2019 Workshop on Challenging problems in Statistical Learning, Apr 2019, Grenoble, France. (poster)

F. Boux, F. Forbes, J. Arbel, E. Barbier. Dictionary learning via regression: vascular MRI application, CNIV 2019 - 3e Congres National d'Imagerie du Vivant, Feb 2019, Paris, France. pp.1-12, (slides)

V. Munoz Ramirez, M. Dojat, F. Forbes. Mixture Models for the characterization of brain abnormalities in "de novo" Parkinsonian patients, CNIV 2019 - 3e Congres National d'Imagerie du Vivant, Feb 2019, Paris, France. pp.1-16, (slides)

F. Boux, F. Forbes, J. Arbel, E. Barbier. Estimation de parametres IRM en grande dimension via une regression inverse. SFRMBM 2019 - 4e congres de la Societe Francaise de Resonance Magnetique en Biologie et Medecine, Mar 2019, Strasbourg, France, (pdf)

V. Munoz Ramirez, F. Forbes, A. Arnaud, E. Moro, M. Dojat. Anomaly detection in the MRI data of newly diagnosed Parkinsonian patients, SFRMBM 2019 - 4e congres de la Societe Francaise de Resonance Magnetique en Biologie et Medecine, Mar 2019, Strasbourg, France, (poster)

Fei Zheng, Stephane Bonnet, Florence Forbes, Manon Jalbert, Sandrine Lablanche, Pierre-Yves Benhamou. Caracterisation de la variabilite glycemique par analyse statistique multivariee, GRETSI 2019, Lille, France. (pdf)

Fei Zheng, Manon Jalbert, Florence Forbes, Stephane Bonnet, Anne Wojtusciszyn et al. Caracterisation de la variabilite glycemique journaliere chez le patient avec diabete de type 1, SFD 2019 - Congres annuel de la Societe Francophone du Diabete, Mar 2019, Marseille, France. (abstract)

F. Forbes and D. Wraith. Robust mixture modelling using skewed multivariate distributions with variable amounts of tailweight. 51e Journees de la Statistique (JdS'2019), May 2019, Nancy, France, (abstract)

O. Commowick, A. Istace, M. Kain, B. Laurent, F. Leray, et al.. Objective Evaluation of Multiple Sclerosis Lesion Segmentation using a Data Management and Processing Infrastructure. Scientific Reports, Nature Publishing Group, 2018, 8 (1). (pdf)

A. Arnaud, F. Forbes, N. Coquery, N. Collomb, B. Lemasson, E. Barbier. Fully automatic lesion localization and characterization: Application to brain tumors using multiparametric quantitative MRI data. IEEE trans. on Medical Imaging 37, 7, July 2018, p. 1678-1689. (pdf)

E. Perthame, F. Forbes and A. Deleforge. Inverse regression approach to robust nonlinear high-to-low dimensional mapping. Journal of Multivariate Analysis, 163, p.1-14, January 2018. (pdf)

C. Maggia, T. Mistral, S. Doyle, F. Forbes, A. Krainik, D. Galanaud, E. Schmitt, S. Kremer, I. Tropres, J-F. Payen,E. Barbier, M. Dojat, Traumatic Brain Lesion Quantification based on Mean Diffusivity Changes. In Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, BrainLes (MICCAI), ed Crimi Aea (Springer International Publishing AG), To appear. (pdf)

F. Forbes. Mixture Models for Image Analysis Sylvia Fruhwirth-Schnatter; Gilles Celeux; Christian P. Robert. Handbook of Mixture Analysis, CRC press, pp.397-418, 2018, (pdf)

P.-A. Rodesch, V. Rebuffel, C. Fournier, F. Forbes, L. Verger, Spectral CT reconstruction with an explicit photon-counting detector model: a one-step approach, in : SPIE Medical Imaging, Houston, United States, February 2018, (pdf)

F. Boux, F. Forbes , J. Arbel , and E. L. Barbier, Dictionary free MR fingerprinting parameter estimation via inverse regression. Joint Annual meeting ISMRM-ESMRMB, June 16-21 2018, Paris. (abstract)

F. Forbes, H. Lu, J. Arbel. Nonparametric Bayesian Priors for Hidden Markov Random Fields, in : JSM 2018 - Joint Statistical Meeting, Vancouver, Canada, July 2018, (pdf)

T. Rahier, S. Marie, S. Girard, F. Forbes. Fast Bayesian Network Structure Learning using Quasi-Determinism Screening JFRB 2018 - 9emes Journees Francophones sur les Reseaux Bayesiens et les Modeles Graphiques Probabilistes, May 2018, Toulouse, France. pp.14-24 (pdf)

Karina Ashurbekova, Sophie Achard, Florence Forbes. Robust structure learning using multivariate T-distributions 50e Journees de la Statistique (JdS'2018), May 2018, Saclay, France. pp.1-6, (pdf)

M. Albughdadi, L. Chaari, J-Y. Tourneret, F. Forbes, P. Ciuciu. A Bayesian Non-Parametric Hidden Markov Random Model for Hemodynamic Brain Parcellation. Signal Processing, Elsevier, 135, p.132-146, June 2017.(pdf)

A. Chiancone, F. Forbes, S. Girard. Student Sliced Inverse Regression. Computational Statistics and Data Analysis,113, p.441-456, September 2017.(pdf)

J. Arias, P. Ciuciu, M. Dojat, F. Forbes, A. Frau-Pascual, T. Perret, J. M. Warnking, PyHRF: A Python Library for the Analysis of fMRI Data Based on Local Estimation of the Hemodynamic Response Function, in : 16th Python in Science Conference (SciPy 2017), Austin, TX, United States, July 2017, [doi:10.25080/shinma-7f4c6e7-006], (pdf)

B. Lemasson, N. Collomb, A. Arnaud, E. L. Barbier, F. Forbes, Monitoring glioma heterogeneity during tumor growth using clustering analysis of multiparametric MRI data, in ISMRM International Society for Magnetic Resonance in Medicine, Honolulu, United States, April 2017,(pdf)

C.-C. Tu, F. Forbes, N. Wang, B. Lemasson, Structured Mixture of linear mappings in high dimension, in : JSM 2017 - Joint Statistical Meeting, Baltimore, United States, July 2017, (pdf)

F. Andriatsitoaina, N. Collomb, A. Arnaud, F. Forbes, J.P. Issartel, C. Loussouarn, E. Garcion, E. L. Barbier, B. Lemasson, Suivi de l'heterogeneite de la croissance de 4 modeles de gliomes par IRM multiparametrique analysee par clustering, in congres national de l'imagerie du vivant, Paris, France, November 2017, (pdf)

B. Lemasson, N. Collomb, A. Arnaud, F. Forbes, E. L. Barbier, Suivi de l'heterogeneite de la croissance des gliomes par IRM multiparametrique analysee par clustering, in SFRMBM Societe Francaise de Resonance Magnetique en Biologie et Medecine, Bordeaux, France, March 2017,(pdf)

I. Gebru, X. Alameda-Pineda, F. Forbes, R. Horaud. EM Algorithms for Weighted-Data Clustering with Application to Audio-Visual Scene Analysis. IEEE Pattern Analysis and Machine Intelligence, December 2016, vol. 38,12, pp. 2402 - 2415.(pdf)

G. Mazo, S. Girard, F. Forbes. A flexible and tractable class of one-factor copulas. Statistics and Computing, September 2016, Volume 26, Issue 5, pp. 965--979.(pdf)

P. Mesejo, S. Saillet, O. David, C. Benar, J.M. Warnking, F. Forbes. A differential evolution-based approach for fitting a nonlinear biophysical model to fMRI BOLD data. IEEE journal of selected topics in signal processing, March 2016, vol. 10, 2, pp. 416-427. (pdf).

F. Forbes. Modelling Structured Data with Probabilistic Graphical models. In Statistics for Astrophysics- Classification and Clustering. Ed. D. Fraix-Burnet and S. Girard. EAS Publications Series, vol. 77, 2016. (pdf)

Christophe Maggia, Senan Doyle, Florence Forbes, Olivier Heck, Irene Tropres, et al.. Assessment of Tissue Injury in Severe Brain Trauma. Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 9556, Springer International Publishing, pp.57-68, Lecture Notes in Computer Science, 978-3-319-30857-9. (pdf)

S. Doyle, F. Forbes, M. Dojat. Automatic multiple sclerosis lesion segmentation with P-LOCUS, in "Proceedings of the 1st MICCAI Challenge on Multiple Sclerosis Lesions Segmentation Challenge Using a Data Management and Processing Infrastructure - MICCAI-MSSEG", 2016, pp. 17-21, (pdf)

A. Deleforge, F. Forbes. Rectified Binaural Ratio: A Complex T-Distributed Feature for Robust Sound Localization. EUSIPCO 2016 (European Signal Processing Conference), Budapest, Hungary, Sept. 2016. (pdf)

E. Perthame, F. Forbes, A. Deleforge, B. Olivier. Non linear robust regression in high dimension. The XXVIIIth International Biometric Conference between July 10-15, 2016.(pdf)

M. Albughdadi, L. Chaari, F. Forbes, J-Y. Tourneret and P. Ciuciu. Multi-subject joint parcellation detection estimation in functional MRI. International Symposium on Biomedical Imaging (ISBI), Prague, April 13-16 2016.(pdf)

Maggia C, Doyle S, Forbes F, Heck O, Tropres I, Berthet C, Teyssier Y, Velly L, Payen J-F, Dojat M. Assessment of Tissue Injury in Severe Brain Trauma. In: Crimi A, Menze B, Maier O, Reyes M, Handels H, editors. Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries: First International Workshop, Brainles 2015, Held in Conjunction with MICCAI 2015, Munich, Germany, October 5, 2015, Springer International Publishing. LNCS 9556 pp. 57-68, 2016. doi 10.1007/978-3-319-30858-6_6. (pdf)

F. Forbes, A. Chiancone, S. Girard, Student sliced inverse regression, in : 9th International Conference of the ERCIM WG on Computational and Methodological Statistics, Seville, Spain, December 2016, (pdf).

E. Perthame, F. Forbes, B. Olivier, A. Deleforge. Regression non lineaire robuste en grande dimension. 48emes JournÈes de Statistique de la SociÈtÈ Francaise de Statistique (SFdS), Montpellier, France, May 2016. (pdf).

F. Forbes, Introduction to statistical methods in signal and image processing. 11th GRETSI Summer School on signal and image processing, Peyresq, July 2016. (site).

G. Mazo, S. Girard, F. Forbes. Weighted least-squares inference based on dependence coefficients for multivariate copulas. ESAIM Probability and Statistics, 19, p.746-765, Oct. 2015. (pdf)HAL

G. Mazo, S. Girard, F. Forbes. A class of multivariate copulas based on products of bivariate copulas. Journal of Multivariate Analysis, 140, 363--376, 2015. (hal) (pdf)

D. Wraith, F. Forbes, Location and scale mixtures of Gaussians with flexible tail behaviour: Properties, inference and application to multivariate clustering. Computational Statistics and Data Analysis, 90:61--73,2015. (preprint-pdf)(supplementary material)(link to journal version)

A. Deleforge, F. Forbes, S. Ba and R. Horaud, Hyper-spectral image analysis with Partially-Latent Regression and spatial Markov dependencies. IEEE journal of selected topics in signal processing, 9(6):1037--1048, 2015. (pre-print pdf)

A. Deleforge, F. Forbes and R. Horaud, Hearing on binaural manifolds: acoustic space learning for sound-source separation and localization. International Journal of Neural Systems, 25(1), 2015. 2016 Award for Outstanding Contributions in Neural Systems -Link.(pre-print pdf)

A. Deleforge, F. Forbes and R. Horaud, High-Dimensional Regression with Gaussian Mixtures and Partially-Latent Response Variables. Statistics and Computing, 25(5):893--911, 2015. (pre-print pdf, Supplementary Material)

P. Mesejo, S. Saillet, O. David, C. Benar, J.M. Warnking, F. Forbes. Estimating biophysical parameters from BOLD signals through evolutionary-based optimization. MICCAI, Munich, Germany, October 2015 (pdf)

A. Frau-Pascual, F. Forbes, P. Ciuciu. Comparison of stochastic and variational solutions to ASL fMRI data analysis. MICCAI, Munich, Germany, October 2015 (pdf)(poster)(teaser)

A. Frau-Pascual, F. Forbes, P. Ciuciu. Variational physiologically informed solution to hemodynamic and perfusion response estimation from ASL fMRI data. Pattern Recognition for Neuroimaging (PRNI'15), Stanford, USA, June 2015 (pdf)(poster)(slides).

A. Frau-Pascual, F. Forbes, P. Ciuciu. Physiological Models Comparison for the Analysis of ASL fMRI Data. 2015 IEEE International Symposium on Biomedical Imaging (ISBI'15), Brooklin, USA, May 2015.(pdf)

A. Arnaud , F. Forbes, N. Coquery, E. Barbier, B. Lemasson. Tumor classification and prediction using robust multivariate clustering of multiparametric MRI. ISMRM 2015 Annual Meeting, Toronto, Canada 2015 (pdf)(poster).

F. Forbes, A. Frau-Pascual, P. Ciuciu. MÈthode d'approximation variationnelle pour l'analyse de donnÈes d'IRM fonctionnelle acquise par Arterial Spin Labelling. GRETSI, Lyon, France, September 2015.(pdf)

A. Arnaud , F. Forbes, B. Lemasson, E. Barbier, . Paquet R pour l'estimation d'un mÈlange de lois de Student multivariÈes a Èchelles multiples. 4emes rencontres R, Grenoble, France, June 2015.(pdf).

A. Arnaud, F. Forbes, B. Lemasson, E. Barbier, N. Coquery. Melanges de lois de Student a echelles Multiples pour la caracterisation de tumeurs par IRM multiparametrique. 47emes Journees de Statistique de la Societe Francaise de Statistique (SFdS), Lille, France, May 2015. (pdf).

A. Arnaud , F. Forbes, N. Coquery, E. Barbier, B. Lemasson. Melanges de lois de Student multivariees generalisees : application a la caracterisation de tumeurs par IRM multiparametrique, in "2eme congres de la SFRMBM (Societe Francaise de Resonance Magnetique en Biologie et Medecine)", Grenoble, France, March 2015.(pdf)(poster).

S. Doyle, B. Lemasson, F. Vasseur, P. Bourdillon, F. Ducray, J. Honnorat, L. Guilloton, J. Guyotat, C. Remy, F. Forbes, F. Cotton, E. Barbier, M. Dojat. Segmentation des tumeurs cerebrales de bas grade par une approche bayesienne : delineation manuelle versus automatique, in "2eme congres de la SFRMBM (Societe Francaise de Resonance Magnetique en Biologie et Medecine)", Grenoble, France, March 2015.(pdf)

P. Ciuciu, F. Forbes, T. Vincent and L. Chaari, Chapter 7 Joint Detection-Estimation in Functional MRI (pages 160-200), in Regularization and Bayesian Methods for Inverse Problems in Signal and Image Processing, Jean-Francois Giovannelli and Jerome Idier Eds., John Wiley and Sons, 2015. (pdf)

T. Vincent, S. Badillo, L. Risser, L. Chaari, C. Bakhous, F. Forbes and P. Ciuciu, Flexible multivariate hemodynamics fMRI data analyses and simulations with PyHRF. Frontiers in Neuroscience, Section Brain Imaging Methods, 8(67), 2014.(pre-print)

F. Forbes and D. Wraith, A new family of multivariate heavy-tailed distributions with variable marginal amounts of tailweights: Application to robust clustering. Statistics and Computing,24(6):971--984, 2014. (pdf) (supplementary)

B. Menze, A. Jakab, S. Bauer et al, The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS). IEEE Transactions on Medical Imaging 34, 10, October 2014, p. 1993- 2024, [doi:10.1109/TMI.2014.2377694], (pdf)

A. Roche and F. Forbes, Partial volume estimation in brain MRI revisited. International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Boston, USA, September 2014.pdf

A. Frau-Pascual, T. Vincent, J. Sloboda, P. Ciuciu and F. Forbes, Physiologically informed Bayesian analysis of ASL fMRI data. MICCAI Worskhop on Bayesian and Graphical Models for Biomedical Imaging, Boston, USA, September 2014.pdf

A. Deleforge, F. Forbes and R. Horaud, Hyper-spectral Image Analysis with Partially-Latent Regression. EUSIPCO (22nd European Signal Processing Conference), Lisbon, Portugal, September 2014. (pre-print pdf)

M. Albughdadi, L. Chaari, F. Forbes, JY. Tourneret and P. Ciuciu, Model Selection for Hemodynamic Brain Parcellation in fMRI, EUSIPCO (22nd European Signal Processing Conference), Lisbon, Portugal, September 2014. (pre-print pdf)

I. dejene Gebru, X. Alameda-Pineda, R. Horaud, F. Forbes, Active Speaker Localization By Multimodal Weighted Data Clustering. IEEE Machine Learning for Signal Processing Workshop, Reims, France, 2014 (selection rate: 60%). pdf

A, Frau, T. Vincent, F. Forbes and P. Ciuciu, Hemodynamically Informed parcellation of cerebral fMRI data. The 39th International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Florence, Italy, May 26 - 31, 2014.pdf

S. Doyle, B. Lemasson, F. Vasseur, P. Bourdillon, F. Ducray, J. Honnorat, L. Guilloton, J. Guyotat, C. Remy, F. Forbes, F. Cotton, E. Barbier, M. Dojat. Comparison of manual versus automatic delineation of low-grade gliomas based on MR brain scans, in "Organization for Human Brain Mapping (OHBM) 2014 Annual meeting", Hambourg, Germany, June 2014

F. Forbes, D. Wraith, Robust mixture modelling using skewed multivariate distributions with variable amounts of tailweight, in : 7th International Conference of the ERCIM WG on Computing and Statistics, Pise, Italy, October 2014, (pdf)

G. Mazo, S. Girard, F. Forbes, A flexible, tractable class of copulas and its estimation, in : COMPSTAT 2014 - 21st International Conference on Computational Statistics, Geneva, Switzerland, August 2014, (pdf)

F. Forbes, A. Deleforge, R. Horaud, High dimensional regression with Gaussian mixtures and partially latent response variables: Application to hyper-spectral image analysis, in : Rencontre d'Astrostatistique, Grenoble, France, November 2014, (pdf)

F. Forbes, M. Charras-Garrido, L. Azizi, S. Doyle and D. Abrial, Spatial risk mapping for rare disease with hidden Markov fields and variational EM, Annals of Applied Statistics, Vol. 7, No. 2, 1192--1216 pdf

L. Chaari, T. Vincent, F. Forbes, M. Dojat and P. ciuciu, Fast joint detection-estimation of evoked brain activity in event-related fMRI using a variational approach, IEEE Transactions on Medical Imaging,32(5):821-837, 2013. (pdf)

M. Charras-Garrido, L. Azizi, F. Forbes, S. Doyle, N. Peyrard, D. Abrial, On the difficulty to clearly identify and delineate disease risk hot spots, International Journal of Applied Earth Observation and Geoinformation, 22:99-105, 2013. (pdf)

T. Vincent, J. Warnking, M. Villien, A. Krainik, P. Ciuciu and F. Forbes, Bayesian Joint Detection-Estimation of cerebral vasoreactivity from ASL fMRI data. International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Nagoya, Japan, September 2013.pdf

V. Khalidov, F. Forbes, R. P. Horaud, Alignment of Binocular-Binaural Data Using a Moving Audio-Visual Target. IEEE International Workshop on Multimedia Signal Processing (MMSP 2013), Pula, Sardinia, Italy, September 30th-October 2nd, 2013.Best Paper Award-Link. pdf

T. Vincent, F. Forbes and P. Ciuciu, Bayesian BOLD and perfusion source separation and deconvolution from functional ASL imaging. The 38th International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Vancouver, Canada, May 26 - 31, 2013.pdf

A. Deleforge, F. Forbes and R. Horaud, Variational EM for Binaural Sound-Source Separation and Localization. The 38th International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Vancouver, Canada, May 26 - 31, 2013. pdf

C. Bakhous, F. Forbes, T. Vincent, M. Dojat and P. Ciuciu, Variational variable selection to assess experimental condition relevance in event-related fMRI. IEEE International Symposium on Biomedical Imaging (ISBI), 4p., April 7-11 2013. pdf

C. Bakhous, F. Forbes, F. Enikeeva, T. Vincent, M. Dojat and P. Ciuciu, Analyse parcimonieuse des donnees díirm fonctionnelle dans un cadre bayesien variationnel. 45emes Journees de Statistique organisees par la Societe Francaise de Statistique, Toulouse. pdf

A. Studeny ; F. Forbes ; E. Coissac ; A. Viari ; L. Zinger ; C. Mercier ; A. Bonin ; F. Boyer ; P. Taberlet, Spatial modelling of plant diversity from high-throughput environmental DNA sequence data. 45emes Journees de Statistique organisees par la Societe Francaise de Statistique, Toulouse. pdf

P. Ciuciu, F. Forbes, T. Vincent and L. Chaari, DÈtection-estimation conjointe en IRM fonctionnelle, in Methodes d'inversion appliquees au traitement du signal et de l'image, Jean-Francois Giovannelli and Jerome Idier Eds., HERMES, 2013. (pdf))

L. Chaari, F. Forbes, T. Vincent and P. Ciuciu, Hemodynamic-informed parcellation of fMRI data in a Joint Detection Estimation framework, International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Nice, France, October 1 - 5, 2012. pdf.

C. Bakhous, F. Forbes, T. Vincent, L. Chaari, M. Dojat and P. Ciuciu, Adaptive experimental condition selection in event-related fMRI. IEEE International Symposium on Biomedical Imaging (ISBI), 4p., May 2-5 2012. pdf,Link

L. Chaari, F. Forbes, T. Vincent and P. Ciuciu. Robust voxel-wise Joint Detection Estimation of brain activity in fMRI, IEEE International Conference on Image Processing (ICIP), Orlando, USA, 4p., September 30 - October 3, 2012. pdf

K. Qin, F. Raimondo, F. Forbes, Yew Soon Ong, An Improved CUDA-Based Implementation of Differential Evolution on GPU, Genetic and Evolutionary Computation Conference 2012 (Gecco 2012), July 12-16, 2011. pdf. Nominated for the best paper award (finalist) in the Digital Entertainment Technologies and Arts / Parallel Evolutionary Systems session.

L. Chaari, F. Forbes, P. Ciuciu, T. Vincent, Parcel-free Joint Detection-Estimation in fMRI, JournÈes de Statistique de la SociÈtÈ FranÁaise de Statistique (SFdS), Brussels, Belgium, 6p., May 21-25, 2012. pdf

C. Bakhous, F. Forbes, T. Vincent, L. Chaari, M. Dojat and P. Ciuciu, SÈlection de variable dans un cadre bayÈsien de traitement de donnÈes d'IRM fonctionnelle, JournÈes de Statistique de la SociÈtÈ FranÁaise de Statistique (SFdS), Brussels, Belgium, 6p., May 21-25, 2012. pdf

F. Forbes, B. Scherrer and M. Dojat, Bayesian Markov model for cooperative clustering: application to robust MRI brain scan segmentation, Journal de la SociÈtÈ FranÁaise de Statistique, Vol. 152 No. 3, 2011. (pdf))

M. Vignes, J. Blanchet, D. Leroux and F. Forbes, SpaCEM3, a software for biological module detection when data is incomplete, high dimensional and dependent, Bioinformatics, 27(6):881-882, 2011. (pdf)

V. Khalidov, F. Forbes, R. P. Horaud, Conjugate Mixture Models for Clustering Multimodal Data, Neural Computation, 23(2):517--557, February 2011. (web site)(pdf)

Horaud, R. and Forbes, F. and Yguel, M. and Dewaele, G. and Zhang, J. Rigid and Articulated Point Registration with Expectation Conditional Maximization. IEEE Trans. on Pattern Analysis and Machine Intelligence, 33(3):587-602, March 2011. (web site)(pdf)

L. Risser, T. Vincent, F. Forbes, J. Idier and P. Ciuciu. Min-max extrapolation scheme for fast estimation of 3D Potts field partition functions. Application to the joint detection-estimation of brain activity in fMRI, Journal of Signal Processing Systems, 65(3):335-338, 2011.(pre-print).

X. Alameda-Pineda, V. Khalidov, R. P. Horaud, F. Forbes, Finding Audio-Visual Events in Informal Social Gatherings, IEEE/ACM International Conference on Multimodal Interfaces (ICMI'11) - November 2011. Outstanding Paper Award. pdf.Web site

L. Chaari, F. Forbes, T. Vincent, M. Dojat, P. Ciuciu, Variational solution to the Joint Detection Estimation of Brain Activity in fMRI, The 14th international conference on Medical Image Computing and Computer Assisted Intervention MICCAI 2011, September 18-22, 2011, Toronto Canada.pdf

K. Qin, F. Forbes, Harmony Search with Differential Mutation Based Pitch Adjustment, Genetic and Evolutionary Computation Conference 2011 (Gecco 2011), July 12-16, 2011. pdf

K. Qin, F. Forbes, Dynamic Regional Harmony Search with Opposition and Local Learning, Genetic and Evolutionary Computation Conference 2011 (Gecco 2011), July 12-16, 2011. pdf and Technical Report version

L. Chaari, F. Forbes, P. Ciuciu, T. Vincent and M. Dojat, Bayesian Variational Approximation for the Joint Detection Estimation of Brain Activity in fMRI, IEEE International Workshop on Statistical Signal Processing 2011 (SSP'11), June 28-30, 2011. pdf

L. Amate, F. Forbes, J. Fontecave-Jallon, B. Vettier, C. Garbay, Probabilistic Model Definition for Physiological State Monitoring, IEEE International Workshop on Statistical Signal Processing 2011 (SSP'11), June 28-30, 2011. pdf

Chaari, L., Forbes, F., Ciuciu, P., Vincent, T., and Dojat, M. A Variational Bayesian approach for the Joint Detection Estimation of Brain Activity in functional MRI. In 43eme JournÈes de la SociÈtÈ FranÁaise de Statistiques. Tunis, Tunisie, May 23-27, 2011. pdf

L. Azizi, F. Forbes, M. Charras-Garrido, D. Abrial and S. Doyle, Initialisation de líalgorithme EM champ-moyen pour les mÈlanges de Poisson pour donnÈes spatiales et application la cartographie du risque en ÈpidÈmiologie. In 43eme JournÈes de la SociÈtÈ FranÁaise de Statistiques. Tunis, Tunisie, May 23-27, 2011.

L. Azizi, F. Forbes, S. Doyle, M. Charras-Garrido and D. Abrial, Spatio-temporal Markov Random Field approach to risk mapping, The 14th Applied Stochastic Models and Data Analysis (ASMDA2011) conference of the ASMDA International Society, Rome, Italy, 7 - 10 June 2011. (abstract)

D. Abrial, L. Azizi, M. Charras-Garrido and F. Forbes, Risk mapping based on hidden Markov random field and variational approximations, 1st Conference on Spatial Statistics 2011 - Mapping Global Change, University of Twente, Enschede, The Netherlands, 2011. (abstract)

M. Vignes, J. Blanchet, D. Leroux and F. Forbes, Clustering of incomplete, high dimensional and dependent biological data with SpaCEM3, Journee satellite MODGRAPH 2010 de JOBIM, Montpellier, France, septembre 2010. (pdf)

D. Abrial, L. Azizi, M. Charras-Garrido and F. Forbes, Approche variationnelle pour la cartographie spatio-temporelle du risque en epidemiologie a l'aide de champs de Markov caches, 42emes Journees de Statistique, mai 2010, Marseille, France. (pdf)

L. Risser, T. Vincent, F. Forbes, J. Idier and P. Ciuciu. How to deal with brain deactivations in the joint detection-estimation framework? Top ranked abstracts at the Human Brain Mapping 2010 conference (HBM 2010), Barcelona, June 6-10. (pdf).

R. Narasimha, E. Arnaud, F. Forbes and R. P. Horaud. Disparity and Normal Estimation through alternating maximization, in International Conference on Image Processing, ICIP 2010, Sept. 26-29, Hong-Kong. (pdf)

F. Forbes, S. Doyle, D. Garcia-Lorenzo, C. Barillot and M. Dojat. A weighted Multi-sequence Markov model for brain lesion segmentation. In Y.W. Teh and M. Titterington (Eds.), Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS) 2010, JMLR:W CP 9, pp 225-232, Chia Laguna, Sardinia, Italy, May 13-15 2010. (pdf)

B. Scherrer, F. Forbes, C. Garbay and M. Dojat. A joint Bayesian framework for MR brain scan tissue and structure segmentation based on distributed Markovian agents. In I. Bichindaritz and eds. L. Jain editors, Computational Intelligence in Healtcare 4. Springer-Verlag, Berlin, 2010. Studies in Computational Intelligence, volume 309. (pre-print).

F. Forbes, S. Doyle, D. Garcia-Lorenzo, C. Barillot and M. Dojat. Adaptive weighted fusion of multiple MR sequences for brain lesion segmentation. IEEE International Symposium on Biomedical Imaging (ISBI), Rotterdam, The Netherlands, 14-17 April 2010. (pdf)

L. Azizi, D.Abrial, M. Charras-Garrido and F. Forbes, spatio-temporal risk Mapping based on Hidden Markov random field and variational approximations, SMTDA, Chania, Crete, 7 - 10 Juin 2010.

M. Vignes and F. Forbes. Genes clustering via Integrated Markov models combining individual and pairwise features. IEEE/ACM trans. on computational biology and bioinformatics, volume 6, number 2, pp.260-270, April-June 2009. (pre-print).

B. Scherrer, M. Dojat, F. Forbes and C. Garbay. Agentification of Markov Model Based Segmentation: Application to MRI Brain Scans. Artificial Intelligence in Medicine (AIM), vol. 46, no.1, pp.81-95, 2009. (pdf).

F. Forbes and W. Pieczynski. New trends in Markov models and related learning to restore data. IEEE international workshop on Machine Learning for Signal Processing (MLSP), September 2-4, 2009, Grenoble, France. (pdf).

J.Blanchet, F. Forbes, S. Chopart and L. Azizi. Le logiciel Spacem3 pour la classification de donnees complexes. La revue Modulad, 40, p. 147--166, 2009. (pdf).

B. Scherrer, F. Forbes, and M. Dojat. A conditional random field approach for coupling local registration with robust tissue and structure segmentation. MICCAI, London, UK, 2009. (pdf)(additional material).

P. Loiseau, P. Goncalves, S. Girard, F. Forbes and P. Primet Vicat-Blanc. "Maximum likelihood estimation of the flow size distribution tail index from sampled packet data", SIGMETRICS - Joint International Conference on Measurement and Modeling of Computer Systems, Seattle, USA, 2009. (pdf).

B. Scherrer, F. Forbes, C. Garbay and M. Dojat. Distributed Local MRF Models for Tissue and Structure Brain Segmentation. IEEE trans. on Medical Imaging, 28(8):1278-1295, 2009. (pdf).

R. Narasimha, E. Arnaud, F. Forbes and R. P. Horaud. A Joint Framework for Disparity and Surface Normal Estimation, Research Report INRIA, RR-7090, Oct., 2009. (Research Report)

J. Blanchet and F. Forbes. Triplet Markov fields for the classification of complex structure data. IEEE trans. on Pattern Analysis and Machine Intelligence, 30(6): 1055-1067, 2008. (pre-print).

Fully Bayesian Joint Model for MR Brain Scan Tissue and Structure Segmentation.(with B. Scherrer, M. Dojat and C. Garbay). Received the Young Investigator Award in Segmentation. MICCAI 2008, New-York, USA, pp. 1066-74. (pre-print)(video)(Software short presentation French and English)(Forum 4i video in French).

Cooperative Disparity and object boundary estimation (with R. Narasimha, E. Arnaud and R. Horaud). 15th International Conference on Image Processing ICIP 2008,i San Diego, USA, pp. 1784-1787. (pre-print).

V. Khalidov, F. Forbes, M. Hansard, E. Arnaud and R. Horaud. Audio-Visual clustering for 3D speaker localization. 5th joint Workshop on Machine Learning and Multimodal Interaction MLMI 2008, Utrecht, The Netherlands, pp. 86-97. (pre-print).

Vasil Khalidov, Florence Forbes, Miles Hansard, Elise Arnaud, Radu P. Horaud. Detection and Localization of 3D Audio-Visual Objects Using Unsupervised Clustering. ACM/IEEE International Conference on Multimodal Interfaces (ICMI 08) - October 2008, pp217-224.(pre-print).

The CAVA corpus : synchronised stereoscopic and binaural datasets with head movements. Elise Arnaud, Heidi Christensen, Yan-Chen Lu, Jon Barker, Vasil Khalidov, Miles Hansard, Bertrand Holveck, Herve Mathieu, Ramya Narasimha, Elise Taillant, Florence Forbes and Radu P. Horaud. ACM/IEEE International Conference on Multimodal Interfaces (ICMI 08) - October 2008, pp. 109-116. (pre-print).

Combining Monte Carlo and Mean field like methods for inference in hidden Markov Random Fields. (With Gersende Fort). IEEE Trans. on Image Processing. March 2007, volume 16, issue 3, pp.824-837. (pre-print).

Chibiao Chen, Eric Durand, Florence Forbes and Olivier Francois. Bayesian clustering algorithms ascertaining spatial population structure: A new computer program and a comparison study. Molecular Ecology Notes, 7(5), pp. 747-756, September 2007. pdf.

MRF Agent based segmentation: Application to MRI brain scans (with B. Scherrer, M. Dojat and C. Garbay). in: A. A. H. R. Bellazzi (Eds.), Proceedings of the AIME conference (Amsterdam July 2007), Spirnger-Verlag, Berlin, 2007, pp. 13-23. . (pre-print).

LOCUS: LOcal Cooperative Unified Segmentation of MRI brain scans (with B. Scherrer, M. Dojat and C. Garbay). MICCAI(1) 2007, pp. 219-227, Brisbane, Australia. (pre-print)(video).

Multimodal MRI segmentation of ischemic stroke lesions (with Y. Kabir, M. Dojat, B. Scherrer and C. Garbay). in: Proceedings of the 29th Annual International Conference of the IEEE Engineering in Medicine and biology Society, EMBC August 2007, Lyon, France. (pre-print).

Deviance Information Criteria for missing data models. With discussion. (with G. Celeux, C.P. Robert and M. Titterington). in Bayesian Analysis, vol.1, number 4, pp 651-706, 2006. (Tech Report version).

Segmentation Markovienne et distribuee d'IRM cerebrales. (with B. Scherrer, M. Dojat and C. Garbay). RFIA janvier 2006, Tours, France. (pre-print).

G. Dewaele, F. Devernay, R. Horaud and F. Forbes. The Alignement Between 3-D Data and Articulated Shapes with Bending Surfaces. European Conference on Computer Vision March 2006 (3), pp.578-591, Austria. (pdf).

Model-based Region-Of-Interest Selection in Dynamic Breast MRI. (With Nathalie Peyrard, Chris Fraley, Dianne Georgian-Smith, David M. Goldhaber and Adrian E. Raftery). February 2006. Journal of Computer Assisted Tomography. (pdf).

Une approche SMA pour la segmentation Markovienne des tissus et structures presents dans les IRM cerebrales. (with B. Scherrer, M. Dojat and C. Garbay). JETIM: 2eme Journees d'Etudes Algero-Francaises en Imagerie Medicale 2006, Algerie. (pre-print).

Distributed and Cooperative Markovian Segmentation of tissues and structures in MRI brain scans. (with B. Scherrer, M. Dojat and C. Garbay). HBM meeting, Florence Italy, June 11-15 2006. (pre-print).

A statistical glance at clustering models to fit biological network and expression data (with M. Vignes). 31st conference on Stochastic Processes and their Applications, Paris, France 2006. .

Integrated Markov models for clustering genes combining individual features and pairwise relationships (with M. Vignes). 4th workshop on Statistical methods for post-genomic data, Toulouse, France. .

Triplet Markov fields designed for supervised classification of textured images (with J. Blanchet). COMPSTAT, 17th symposium of the IASC, Roma, Italy, August 2006. (Poster).

Chibiao Chen, Florence Forbes, Olivier Francois. FASTRUCT: Model-based clustering made faster. Molecular Ecology Notes, 6, pp. 980-983, 2006. pdf.

Champs de Markov caches et fusion de donnees individuelles et pairees pour l'identification de groupes de genes (avec M. Vignes). Juillet 2005. JOBIM, Lyon, France, 2005. .

Markov random fields for textures recognition with local invariant regions and their geometric relationaships. (with J. Blanchet and C. Schmid). British Machine Vision Conference. September 2005, Oxford, UK. (pre-print).

J. Blanchet, F. Forbes and C. Schmid. Modeles markoviens pour l'organisation spatial de descripteurs d'images. 7eme conference francophone sur l'apprentissage automatique (CAP) 2005, Presses Universitaires de Grenoble, pp. 113-126. (pre-print).

J. Blanchet, F. Forbes and C. Schmid. Markov random fields for recognizing textures modeled by feature vectors, International Conference on Applied Stochastic Models and Data Analysis, Brest, France, May 2005. (pre-print).

N. Peyrard, F. Forbes and D. Allard. Comparaison de deux modelisations pour la classification de donnees geostatistiques. 37eme journees de statistiques organisees par la Societe Francaise de Statistique. Pau, Juin 2005. (ps),(slides).

Modele de Potts avec champ externe et algorithme de type EM pour la segmentation d'image (with G. Celeux and N. Peyrard). RFIA janvier 2004, Toulouse, France. (pre-print). English version: EM-based image segmentation using Potts models with external field. (postcript file).

EM procedures using mean field-like approximations for Markov model-based image segmentation (with G. Celeux and N. Peyrard). Pattern Recognition, 36:1, pp. 131-144, 2003. (pre-print postscript file).

Hidden Markov Random Field Selection Criteria based on Mean Field-like approximations (with N. Peyrard). IEEE trans. on Pattern Analysis and Machine Intelligence, vol.25, no.9, August 2003, pp. 1089-1101. (pdf).

A Component-wise EM Algorithm for Mixtures (with G. Celeux, S. Chretien and A. Mkhadri). Journal of Computational and Graphical Statistics. 10,p.699--712, December 2001. (pre-print postscript file).

Bayesian Morphology: Fast Unsupervised Bayesian Image Analysis (with A. E. Raftery). Journal of American Statistical Association, vol. 94, no 446, Theory and Methods (1999). (pre-print postscript file).

Spatial Statistical Analysis of Breast Magnetic Resonance Images via Model-based Clustering, Morphology and Markov Random Fields (with C. Fraley, N. Peyrard, A.E. Raftery). Report for Toshiba inc. 1999. (postscript file).

Region-Of-Interest Selection and Statistical Analysis of Dynamic Breast Magnetic Resonance Imaging Data (with C. Fraley, D. Georgian-Smith, D. M. goldhaber, N. Peyrard and A. Raftery). Technical report Inria Rhone-Alpes,RR-4249,http://www.inria.fr/rrrt/rr-4249.html .

Counting stable sets on Cartesian products of graphs (with B. Ycart). Discrete Mathematics, 186 (1998), no.1-3, 105-116. (pre-print postscript file).

Increasing couplings for interacting particle systems (with O. Francois). C.R. Acad. Sci. Paris, Tome 324, Série I, Rubrique Probabilités, no.4, 459--464(1997). (pre-print postscript file).

Stochastic comparison for Markov processes on a product of partially ordered sets" (with O. Francois). Statist. Probab. lett. 33 (1997), no.3, 309--320. (pre-print postscript file).

PhD Thesis (in French), Modèles markoviens de ressources partagées , University Joseph Fourier, Grenoble I, September 1996. (postscript file).

The philosophers' process on ladder graphs (with B. Ycart). Comm. Statist. Stochastic Models 12 (1996), no.4, 559--583. (pre-print postscript file).

Stochastic comparison for resource sharing models (with O. Francois and B. Ycart). Markov Processes and Related Fields 2 (1996), no.4, 581--605. (pre-print postscript file).