Speaker
Prof.
Matteo Marsili
(Abdus Salam ICTP)
Description
I will present a general framework which can be used to
reconstruct probability distributions for strings of binary
variables. While the problem of inference can be analytically
controlled for small systems, a description of some of the
regularization prescriptions needed to treat large systems
will be provided, together with a discussion concerning their
symmetries. Finally, I will present several possible
applications of these methods, namely i) exact, fast
inference for 1-D periodic systems, ii) exact, fast inference
for tree-like graphs, iii) approximate, fast inference for
generic graphs.
Primary author
Prof.
Matteo Marsili
(Abdus Salam ICTP)
