G e o S t a t
Geometry & Statistics in acquisition data
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GeoStat is an INRIA project located at INRIA Bordeaux Sud-Ouest (INRIA BSO), inside the theme: applied mathematical computation and simulation, optimization, learning and statistical methods.


The team makes fundamental and applied research in the analysis of complex natural signals using paradigms and methods from Statistical Physics such as: scale invariance, predictability, universality classes We study the parameters related to common statistical organization in different complex signals and systems, we derive new types of sparse and compact representations, and machine learning approaches. We are also developing tools for the analysis of complex signals that better match the statistical and geometrical organisation inside these data: as a typical example, we cite the evaluation of cascading properties of physical variables inside complex signals.

GeoStat's research thematics are centered on the following theoretical developments:

  • Signal processing using methods from complex systems and statistical physics,
  • Sparse and compact representations, signal reconstruction, machine learning,
  • Predictability in complex systems,
  • Analysis, classification, detection in complex signals.

and the following applied objectives:

  • Analysis of complex and turbulent signals in earth observation, universe sciences and remote sensing.
  • Complex dynamics in the analysis of heartbeat signals.
  • Speech analysis.
  • Super-resolution.
  • Non convex optimization methods (3 years contract with i2S company).


GeoStat is a member of GDR PHENIX.

GeoStat is a member of GDR ISIS.

GeoStat is a member of GDR AMF.

Last Updated on Monday, 09 October 2017 14:08