19 citations · 53 across the 9 of their papers we have counts for
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cs.LG2022★ 3 cited
Identifying Differential Equations to predict Blood Glucose using Sparse Identification of Nonlinear Systems
David Jödicke, Daniel Parra, Gabriel Kronberger +1
Describing dynamic medical systems using machine learning is a challenging topic with a wide range of applications. In this work, the possibility of modeling the blood glucose leve…
cond-mat.mtrl-sci2022★ 6 cited
Symbolic Regression in Materials Science: Discovering Interatomic Potentials from Data
Bogdan Burlacu, Michael Kommenda, Gabriel Kronberger +2
Particle-based modeling of materials at atomic scale plays an important role in the development of new materials and understanding of their properties. The accuracy of particle sim…