Speaker
Marco Selig
(MPA Garching)
Description
This Tutorial introduces NIFTY, "Numerical Information Field Theory",
which allows a user an abstract formulation and programming of SIGNAL
inference AND IMAGE RECONSTRUCTION algorithms. NIFTY is a versatile Python
library designed to enable the development of signal inference algorithms
that operate regardless of the underlying spatial grid and its resolution.
The Tutorial covers the simulation of mock data from Gaussian random
processes and a Wiener filter reconstruction of the underlying signal
field from this data set. Using NIFTY, this filter can be applied on a
variety of spaces; e.g., point sets, n-dimensional regular grids,
spherical spaces, their harmonic counterparts, and product spaces
constructed as combinations of those.
