3 papers
cond-mat.mtrl-sci2025
Causal Discovery from Data Assisted by Large Language Models
Kamyar Barakati, Alexander Molak, Chris Nelson +3
Knowledge driven discovery of novel materials necessitates the development of the causal models for the property emergence. While in classical physical paradigm the causal relation…
cond-mat.supr-con2025
Rapid analysis of point-contact Andreev reflection spectra via machine learning with adaptive data augmentation
Dongik Lee, Valentin Stanev, Xiaohang Zhang +3
Delineating the superconducting order parameters is a pivotal task in investigating superconductivity for probing pairing mechanisms, as well as their symmetry and topology. Point-…
cond-mat.mtrl-sci2024
Reward driven workflows for unsupervised explainable analysis of phases and ferroic variants from atomically resolved imaging data
Kamyar Barakati, Yu Liu, Chris Nelson +4
Rapid progress in aberration corrected electron microscopy necessitates development of robust methods for the identification of phases, ferroic variants, and other pertinent aspect…