Efficient representation of quantum many-body states on classical comput...
Quantum Annealing (QA) was originally intended for accelerating the solu...
As a wide variety of quantum computing platforms become available, metho...
The usual setting for learning the structure and parameters of a graphic...
We address the problem of learning of continuous exponential family
dist...
Drawing independent samples from high-dimensional probability distributi...
Graphical models are widely used in science to represent joint probabili...
Despite strong connections through shared application areas, research ef...
Ensuring secure and reliable operations of the power grid is a primary
c...
Graphical models are useful tools for describing structured high-dimensi...
We consider the problem of reconstructing the dynamic state matrix of
tr...
Optimal power flow (OPF) is the central optimization problem in electric...
We consider the problem of learning the underlying graph of an unknown I...