Computational Information Geometry for Image and Signal Processing

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Computational Information Geometry for Image and Signal Processing

 21 - 25 Sep 2015

ICMS, 15 South College Street Edinburgh

  • Frank Critchley, The Open University
  • Kit Dodson, University of Manchester
  • Frank Nielsen, École Polytechnique & Sony Computer Science Laboratories

About:

This workshop focused on the application and development of information geometric methods in the analysis, classification and retrieval of images and signals, particularly for medical applications. This area of work has developed rapidly over recent years, propelled by the major theoretical developments in information geometry, efficient data and image acquisition (particularly in biological/medical contexts and image recognition) and the desire to process and interpret large databases of digital information.

Photos are available here.

Speakers

  • Frank Critchley and Paul Marriott, Open University & University of Waterloo - Information Geometry and Its Applications: An Overview

  • Frank Nielsen, École Polytechnique & Sony Computer Science Laboratories - Introduction to Computational Information Geometry and Its Applications

  • Shinto Eguchi, Institute of Statistical Mathematics - Spontaneous Learning for Data Distributions via Minimum Divergence

  • Frederic Barbaresco, Thales Land and Air Systems - Koszul/Souriau Models of Information Geometry: Applications to Radar Processing, Current State and Future

  • Alvina Goh, National University of Singapore - Applications to Medical Imaging, Current State and Future Needs

  • Shun-ichi Amari, RIKEN Brain Science Institute - Applications in Cognition and Learning: Current State and Future Needs

  • Nihat Ay, Max Planck Institute for Mathematics in the Sciences - Information-Geometric structures in Cognitive Systems Research

  • Kit Dodson, Manchester University - Information Distance Estimation Between Mixtures of Multivariate Gaussian

  • Germain Van Bever, Open University - Computational Information Geometry for Mixture Models

  • Christophe Saint-Jean, La Rochelle University - Online Mixture Modelling               

  • Nigel Newton, University of Essex - An Information Geometric Representation for Nonlinear Filters

  • Giovanni Pistone, Collegio Carlo Alberto - Information Geometry via the Statistical Bundle With an Example

  • Hiroshi Matsuzoe, Nagoya Institute of Technology - Geometry of Anomalous Statistics and Its Application to Computational Anatomy  

  • Olivier Schwander, LIP6, UPMC) - Comix: Joint Estimation of Mixture Models     

  • Grant Mair, University of Edinburgh - Medical imaging of the brain

  • Gabriel Peyré, Université Paris-Dauphine - Entropic Regularization of Wasserstein Barycenters

  • František Matúš, Institute of Information Theory - On the Boundaries of Exponential Families

  • Bill Sampson, University of Manchester - Dimensionality Reduction for Characterization of Surface Topographies

  • Adrian M Peter, Florida Institute of Technology - Geometry of Orthogonal-Series, Square-Root Density Estimators: Model Selection and Computer Vision Applications

  • Karim Anaya-Izquierdo, University of Bath - Approximate Cuts for Statistical

  • Damiano Brigo, Imperial College London - Stochastic Nonlinear Filtering via Hellinger or L2 Direct Projection on Exponential or Mixture Statistical Manifolds     

  • Atsumi Ohara, University of Fukui - Information Geometry on Multivariate Generalized Gaussian Densities and Its Group Invariance

  • Shun-ichi Amari, RIKEN Brain Science Institute - Information Integration and Complexity of System 

  • Marti Gautier, École Polytechnique France/ Hellebore Capital Management - On Clustering Financial Time Series

  • Frank Nielsen, École Polytechnique & Sony Computer Science Laboratories - Introduction to Computational Information Geometry and Its Applications    

  • Paul Vos, East Carolina University - One and Two Dimensional Exponential Families in the Simplex

  • Radka Sabolova, Open University - Computational Information Geometry for Sparse Goodness-Of-Fit Testing

  • Roman Belavkin, University of Middlesex - Topological Consequences of Asymmetry of Information

  • Michael Betancourt, University College London - The Geometric Foundations of Hamiltonian Monte Carlo

  • Jun Zhang, The University of Michigan - Symplectic and (Para)-Kahler Structures on Statistical Manifolds  

  • Simon Byrne, University College London - Geometry and Ergodicity

  • Asuka Takatsu, Tohuko University - Behaviors of Varphi-Gaussian Measures in Wasserstein Geometry

  • Arleta Szkola, Max Planck Institute for Mathematics in the Sciences - Statistical Models of Density Matrices

  • Richard Nock, NICTA - Optimal Filters on Statistical Manifolds

  • John Armstrong, Kings College London - Optimal Filters on Statistical Manifolds