Riihimaki, HenriLicón Saláiz, José2021-03-102021-03-102019-09-16Riihimaki, H & Licón Saláiz, J 2019, 'Metrics for Learning in Topological Persistence', Paper presented at Applications of Topological Data Analysis, Würzburg, Germany, 16/09/19 - 16/09/19. https://doi.org/10.20392/51hn-fj12workshophttps://hdl.handle.net/2164/16009Acknowledgments We gratefully acknowledge Roel Neggers for providing the DALES simulation data. JLS acknowledges support by the DFG-funded transregional research collaborative TR32 on Patterns in Soil–Vegetation–Atmosphere Systems.161206551engPersistent homologyTopological learningStable rankAtmospheric scienceQA MathematicsQAConference paper10.20392/51hn-fj12https://sites.google.com/view/atda2019/papershttps://sites.google.com/view/atda2019/papershttps://drive.google.com/file/d/1mSjniOKzDMm1a7D7amZPGCW-O3lZXOvn/view