1 citations · 1 across the 3 of their papers we have counts for
3 papers
Exploring Noncollinear Magnetic Energy Landscapes with Bayesian Optimization
Jakob Baumsteiger, Lorenzo Celiberti, Patrick Rinke +2
The investigation of magnetic energy landscapes and the search for ground states of magnetic materials using ab initio methods like density functional theory (DFT) is a challenging…
Active Learning of Molecular Data for Task-Specific Objectives
Kunal Ghosh, Milica Todorović, Aki Vehtari +1
Active learning (AL) has shown promise for being a particularly data-efficient machine learning approach. Yet, its performance depends on the application and it is not clear when A…
Structural disorder by octahedral tilting in inorganic halide perovskites: New insight with Bayesian optimization
Jingrui Li, Fang Pan, Guo-Xu Zhang +8
Structural disorder is common in metal-halide perovskites and important for understanding the functional properties of these materials. First-principles methods can address structu…