A model-independent determination of the Hubble constant from lensed
  quasars and supernovae using Gaussian process regression
  Strongly lensed quasar systems with time delay measurements provide "time
delay distances", which are a combination of three angular diameter distances
and serve as powerful tools to determine the Hubble constant $H_0$. However,
current results often rely on the assumption of the $\Lambda$CDM model. Here we
use a model-independent method based on Gaussian process to directly constrain
the value of $H_0$. By using Gaussian process regression, we can generate
posterior samples of unanchored supernova distances independent of any
cosmological model and anchor them with strong lens systems. The combination of
a supernova sample with large statistics but no sensitivity to $H_0$ with a
strong lens sample with small statistics but $H_0$ sensitivity gives a precise
$H_0$ measurement without the assumption of any cosmological model. We use four
well-analyzed lensing systems from the state-of-art lensing program H0LiCOW and
the Pantheon supernova compilation in our analysis. Assuming the Universe is
flat, we derive the constraint $H_0=72.2 \pm 2.1\,$km/s/Mpc, a precision of
$2.9\%$. Allowing for cosmic curvature with a prior of $\Omega_{k}=[-0.2,0.2]$,
the constraint becomes $H_0=73.0_{-3.0}^{+2.8}\,$km/s/Mpc.
