CLUE: uncertainty-aware artificial intelligence in materials science

Cibrán López, Edgardo Saucedo, Claudio Cazorla

Keywords: machine learning, uncertainty quantification, materials science

TL;DR: This work introduces CLUE, a novel latent space-based method for uncertainty estimation in AI-driven materials science, addressing key challenges and enabling uncertainty-aware applications.

Confirmation Of Submission Requirements: I submit an abstract. It uses the template provided on the submission page and is no longer than 2 pages.

Submission Number: 18