Before revision: Persistence diagrams (PDs) are now routinely used to summarize the underlying topology of sophisticated dataencountered in challenging learning problems . Despite several appealing properties, integrating PDs in learning pipelines can be challenging because their natural geometry is not Hilbertian.
After revision: Persistence diagrams (PDs) are now routinely used to summarize the underlying topology of complex data . Despite several appealing properties, integrating PDs in learning pipelines can be challenging because their natural geometry is not Hilbertian.