Abstract: The overall goal of the paper is to develop a deep kernel principal component analysis (KPCA) for time-dependent data that are nonlinearly distributed in high dimensions. Instead of ...

A Python module to model, fit, and analyse single and binary spectral energy distributions (SEDs). This theory behind the code, and the method it implements, are ...

Abstract: Principal Component Analysis (PCA) aims to acquire the principal component space containing the essential structure of data, instead of being used for mining and extracting the essential ...