Publikationen von Lucas Foppa

Foppa, L.: Beyond a Single Description in Subgroup Discovery of Exceptional Materials: Coherent Collections of Rules Clustered by Similarity. NOMAD Workshop, Data-centric Cruising for New and Novel Materials, Mechanisms, and Insights, Kiel, Germany (2022)

Foppa, L.: Clean Experimental Data for Artificial Intelligence – A Key to Decoding Materials Genes in Heterogeneous Catalysis. The 27th North American Catalysis Society Meeting (NAM27), New York, NY, USA (2022)

Foppa, L.: Materials Genes of Selective Oxidation From Clean Experiments and Artificial Intelligence. Symposium, FUNCAT/Center2Center Meeting, Berlin, Germany (2022)

Foppa, L.: Hierarchical Symbolic Regression for Identifying Key Physical Parameters Correlated With Materials Properties. Seminar, Cardiff University, Online Event (2022)

Foppa, L.: Materials Genes of Heterogeneous Catalysis From Clean Experiments and Artificial Intelligence. 8th UK Catalysis Conference (UKCC2022), Loughborough, UK (2022)

Foppa, L.: Identifying the Materials Genes of Heterogeneous Catalysis With Clean Experiments and Tailored Artificial Intelligence. Colloquium, ETH Zurich, Department of Chemistry and Applied Biosciences, Online Event (2021)

Mauß, J. M.; Kley, K. S.; Khobragade, R.; Tran, N. K.; De Bellis, J.; Schüth, F.; Scheffler, M.; Foppa, L.: Modelling the Time-Dependent Reactivity of Catalysts by Experiments and Artificial Intelligence. (2025)

Sugathan Nair, A.; Foppa, L.; Scheffler, M.: Materials-Discovery Workflows Guided by Symbolic Regression: Identifying Acid-Stable Oxides for Electrocatalysis. (2024)

Behler, J.; Csanyi, G.; Foppa, L.; Kang, K.; Langer, M. F.; Margraf, J. T.; Sugathan Nair, A.; Purcell, T. A. R.; Rinke, P.; Scheffler, M. et al.; Tkatchenko, A.; Todorovic, M.; Unke, O. T.; Yao, Y.: Workflows for Artificial Intelligence. (2024)

Foppa, L.; Scheffler, M.: Coherent Collections of Rules Describing Exceptional Materials Identified with a Multi-Objective Optimization of Subgroups. (2024)

Boley, M.; Luong, F.; Teshuva, S.; Schmidt, D. F.; Foppa, L.; Scheffler, M.: From Prediction to Action: The Critical Role of Proper Performance Estimation for Machine-Learning-Driven Materials Discovery. (2023)

Foppa, L.; Scheffler, M.: Towards a Multi-Objective Optimization of Subgroups for the Discovery of Materials with Exceptional Performance. (2023)