  Bottomonium states are key probes for experimental studies of the quark-gluon
plasma (QGP) created in high-energy nuclear collisions. Theoretical models of
bottomonium productions in high-energy nuclear collisions rely on the in-medium
interactions between the bottom and antibottom quarks. The latter can be
characterized by the temperature ($T$) dependent potential, with real
($V_R(T,r)$) and imaginary ($V_I(T,r)$) parts, as a function of the spatial
separation ($r$). Recently, the masses and thermal widths of up to $3S$ and
$2P$ bottomonium states in QGP were calculated using lattice quantum
chromodynamics (LQCD). Starting from these LQCD results and through a novel
application of deep neural network, here, we obtain $V_R(T,r)$ and $V_I(T,r)$
in a model-independent fashion. The temperature dependence of $V_R(T,r)$ was
found to be very mild between $T\approx0-334$~MeV. For $T=151-334$~MeV,
$V_I(T,r)$ shows a rapid increase with $T$ and $r$, which is much larger than
the perturbation-theory-based expectations.
