Over the last few decades, it has become common to treat data as samples belonging to geometric manifolds or more general nonlinear metric spaces. Together with increasing computer power, this has opened the way to new acquisition and representation methods, and to new data processing techniques; leading to very challenging theoretical and practical questions which require an interplay between differential and metric geometries, optimization, PDEs, stochastic analysis, and computer science.
This workshop aims to bring together leading experts in these fields and young researchers to exchange ideas, create synergies,and enhance current and outline future directions of research.
This workshop will include a poster session; a request for posters will be sent to registered participants in advance of the workshop.
(Universität Wien, Geometry)
Ron Kimmel (Technion - Israel Institute of Technology, Intel Perceptual Computing)
Simon Masnou (Université de Lyon I)
Gabriele Steidl (Universität Kaiserslautern)