  We develop a set of machine-learning interatomic potentials for elemental V,
Nb, Mo, Ta, and W using the Gaussian approximation potential framework. The
potentials show good accuracy and transferability for elastic, thermal, liquid,
defect, and surface properties. All potentials are augmented with accurate
repulsive potentials, making them applicable to radiation damage simulations
involving high-energy collisions. We study melting and liquid properties in
detail and use the potentials to provide melting curves up to 400 GPa for all
five elements.
