31 citations · 31 across the 2 of their papers we have counts for
2 papers
cond-mat.mtrl-sci2025
Combining feature-based approaches with graph neural networks and symbolic regression for synergistic performance and interpretability
Rogério Almeida Gouvêa, Pierre-Paul De Breuck, Tatiane Pretto +2
This study introduces MatterVial, an innovative hybrid framework for feature-based machine learning in materials science. MatterVial expands the feature space by integrating latent…
cond-mat.mtrl-sci2021★ 31 cited
Robust model benchmarking and bias-imbalance in data-driven materials science: a case study on MODNet
Pierre-Paul De Breuck, Matthew L. Evans, Gian-Marco Rignanese
As the number of novel data-driven approaches to material science continues to grow, it is crucial to perform consistent quality, reliability and applicability assessments of model…