  Many-body calculations at the two-particle level require a compact
representation of two-particle Green's functions. In this paper, we introduce a
sparse sampling scheme in the Matsubara frequency domain as well as a tensor
network representation for two-particle Green's functions. The sparse sampling
is based on the intermediate representation basis and allows an accurate
extraction of the generalized susceptibility from a reduced set of Matsubara
frequencies. The tensor network representation provides a system independent
way to compress the information carried by two-particle Green's functions. We
demonstrate efficiency of the present scheme for calculations of static and
dynamic susceptibilities in single- and two-band Hubbard models in the
framework of dynamical mean-field theory.
