Combining feature-based approaches with graph neural networks and symbolic regression for synergistic performance and interpretability.

Pierre-Paul De Breuck

Rogério Almeida Gouvêa Pierre-Paul De Breuck Tatiane Pretto Gian-Marco Rignanese Marcos José Leite Santos Combining feature-based approaches with graph neural networks and symbolic regression for synergistic performance and interpretability. 2025 September abs/2509.03547 CoRR https://doi.org/10.48550/arXiv.2509.03547 db/journals/corr/corr2509.html#abs-2509-03547 streams/journals/corr

Théo Cavignac Jonathan Schmidt 0003 Pierre-Paul De Breuck Antoine Loew Tiago F. T. Cerqueira Haichen Wang Anton Bochkarev Yury Lysogorskiy Aldo H. Romero Ralf Drautz Silvana Botti Miguel A. L. Marques AI-Driven Expansion and Application of the Alexandria Database. 2025 December abs/2512.09169 CoRR https://doi.org/10.48550/arXiv.2512.09169 db/journals/corr/corr2512.html#abs-2512-09169 streams/journals/corr

Pierre-Paul De Breuck Small datasets, big predictions: learning methods for uncertainty-aware modelling of multi-fidelity material properties. 2024 Catholic University of Louvain, Louvain-la-Neuve, Belgium http://hdl.handle.net/2078.1/286595 https://www.base-search.net/Record/24a5f2b3fb9ebb936d3546454f76454758f30eab35d7644ad116fd9aa75f2411 base-search.net (ftunivlouvain:oai:dial.uclouvain.be:boreal:286595) Anton Bochkarev Silvana Botti Théo Cavignac Tiago F. T. Cerqueira Ralf Drautz Rogério Almeida Gouvêa Antoine Loew Yury Lysogorskiy Miguel A. L. Marques Tatiane Pretto Gian-Marco Rignanese Aldo H. Romero Marcos José Leite Santos Jonathan Schmidt 0003 Haichen Wang