Fig. 2. ML-aided HTVS. (a) In practical HTVS based on elemental substitution, newly substituted materials require costly DFT structure relaxations before evaluating functionality. As a way to bypass structure relaxations, property prediction ML models can be augmented with uncertainty quantification incurred by the use of unrelaxed geometry. (b) Generative models can be used to produce new hypothetical crystal structures for HTVS that go beyond the existing structural motifs.