3 papers
cond-mat.mtrl-sci2024
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…
cs.LG2024
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…
cond-mat.mtrl-sci2024
Question Answering models for information extraction from perovskite materials science literature
M. Sipilä, F. Mehryary, S. Pyysalo +2
Scientific text is a promising source of data in materials science, with ongoing research into utilising textual data for materials discovery. In this study, we developed and teste…