Modèles aléatoires et applications

Second workshop on Gaussian Processes at Saint-ÉtienneModèles aléatoires et apllications

Faculté des Sciences et Techniques
Salle A 14

Workshop to the Institute Camille Jordan

 

Second workshop on Gaussian Processes at Saint-Étienne:
Modèles aléatoires et applications

 

 

Aim of the workshop

  "Among many models, the Gaussian ones play a particular role. The central limit theorem for a sequence of real random variables leads naturally to consider Gaussian models. These also are fundamental in basic statistics like for the application of the chi2-test of adequation (with estimation of the parameters). After several decades of intense research, they appear to be central in many other contexts.

    One of its significant appearances is through the Brownian motion (or its derivative'' the white noise). In stock exchange, in fluid mechanic or in neuroscience, we are able to explain the small local perturbations which appear to behave quasi-randomly with the Brownian motion.

    However, it would be extremely reductive to see the Gaussian model only through this point of view. Indeed, theoretically these models have become more and more sophisticated and well understood. Moreover, they have been considerably extended to a larger framework (computer vision, big data, machine learning...).

    The first idea of Gaussian models that we have in mind for this workshop is about the different applications involving Gaussian processes and Gaussian fields. Let us give some example: periodicity detection by Fourier basis (using the self-reproducing Hilbert space) or the modelisation of the retina of the eye (with different parameters in function of the illness of the eye).

    The second idea would be to enrich the model with latent variable. These are classical tools now in machine learning for regression and classification. Its variant, the Gaussian process dynamical model, has been used in computer vision for motion analysis and dynamical texture synthesis. Among these models, we find the stochastic differential equations (with or without latent variable). We have in mind the example of Kalman-Bucy filter which realizes gaussian filtering. This model is used in sciences of ocean and athmosphere, in research about petroleum sources...

    Other subjects of interest for the workshop are Gaussian Processes state-space model, short and long memory processes, without any restriction.

    In the continuity of the First workshop on Gaussian Processes at Saint-Étienne, the aim of this workshop is to gather different researchers from different communities working in the area of the Gaussian Processes, from the theoretical point of view to the applications. "

Poster of the workshop

 

Organizing committee

  • Olvier Alata, Laboratoire Hubert Curien
  • Xavier Bay, ENSMSE
  • Laurence Grammont,  Institut Camille Jordan
  • Romain Ravaille, Institut Camille Jordan
  • Julian Tugaut, Institut Camille Jordan
  • Pascale Villet, Institut Camille Jordan

 

List of confirmed speakers

 

Program

The Schedule
Workshop Program

 

Participants

Olivier ALATA, Laboratoire Hubert Curien
Abdourrahmane ATTO, University Savoie Mont Blanc
Dario AZZIMONTI, IDSIA
François BACHOC, University of Toulouse
Xavier BAY, ENSMSE
Mahdi BOUKROUCHE, University of Saint-Etienne
Lehel CSATO, Universitatea Babes-Bolyai
Masoumeh DASHTI, University of Sussex
Pierre DEL MORAL, University of Bordeaux
Nicolas DURRANDE, Prowler, United Kingdom
Youssef EL HABOUZ, IBN ZOHR Agadir
Rémi EMONET, University of Saint-Etienne
David GAUDRIE, ENSMSE
Léo GAUTHERON, University of Saint-Etienne
Laurence GRAMMONT, University of Saint-Etienne
Daniel HERNANDEZ-LOBATO, Universidad Autónoma de Madrid
Tanguy KERDONCUFF, Laboratoire Hubert Curien
Charlotte LACLAU, University of Saint-Etienne
Charles LESNIEWSKA, University Savoie Mont Blanc
Andrès Felipe LOPEZ LOPERA, ENSMSE
Stéphane MOTTIN, CNRS, UJM, UdL, IOGS
Laetitia Paoli, University of Saint-Etienne
Romain RAVAILLE, University of Saint-Etienne
Levgen REDKO, University of Saint-Etienne
Damien ROBISSOUT, University of Saint-Etienne
Olivier ROUSTANT, ENSMSE
Emmanuel ROUX, University of Saint-Etienne
Didier RULLIERE, University Lyon 1
Hugh SALIMBENI, Imperial College London
Christoper SALINAS, University of Saint-Etienne
Mathieu SART, University of Saint-Etienne
Marc SEBBAN, University of Saint-Etienne
Julian TUGAUT, University of Saint-Etienne
Rémi VIOLA, University of Saint-Etienne

 

 Slides

    (To be announced soon)

 

Inscriptions 

For your inscription, click HERE(before the deadline : Thursday, September 27th)
Registrations are closed.

 

Poster Session

Daniel HERNANDEZ-LOBATO: Approximate Inference in Deep Gaussian Processes by Minimizing Alpha Divergences
Charles LESNIEWSKA: Multivariate Possibility Distributions
Andrés Felipe LOPEZ LOPERA: Gaussian process regression models under linear inequality conditions
Stéphane MOTTIN: Analytical solutions with Legendre integral transform of Spherical Laplace equation & Gaussian processes
Romain RAVAILLE: Wavelet Decomposition of a gaussian process kernel

 

Practical informations

  • The talks will take place in the Faculty of Sciences, room A 14, 23 rue du Docteur Paul Michelon, Saint-Étienne.

  • Venue: Address: Institut Camille Jordan, Faculté des Sciences et Techniques, 23 rue du Docteur Paul Michelon, 42023 Saint-Étienne Cedex 2
  • How to go from the main station Saint-Etienne Chateaucreux to the Institute Camille Jordan:
    The city bus company: STAS: http://www.reseau-stas.fr/fr/itineraires/4/JourneyPlannerThe Bus line M4 takes you from the main train station (Saint-Etienne Châteaucreux) to the faculty of Sciences.
    And bus line M6  takes you from the heart of the city, square Violette, to the faculty.

  • Stay : You will find here a selection of hotels in the center of the city.

 



 

                          

 

 

Contacts

Olivier ALATA, Xavier BAY, Laurence GRAMMONT, Romain RAVAILLE, JulianTUGAUT et Pascale VILLET
workshopgp2018 @ univ-st-etienne.fr