  This paper evaluates heterogeneous information fusion using multi-task
Gaussian processes in the context of geological resource modeling.
Specifically, it empirically demonstrates that information integration across
heterogeneous information sources leads to superior estimates of all the
quantities being modeled, compared to modeling them individually. Multi-task
Gaussian processes provide a powerful approach for simultaneous modeling of
multiple quantities of interest while taking correlations between these
quantities into consideration. Experiments are performed on large scale real
sensor data.
