Martian time-series unraveled: A multi-scale nested approach with factorial variational autoencoders

arXiv:2305.16189v3 Announce Type: replace
Abstract: Unsupervised source separation involves unraveling an unknown set of source signals recorded through a mixing operator, with limited prior knowledge about the sources, and only access to a dataset of signal mixtures. This problem is inherently ill-posed and is further challenged by the variety of timescales exhibited by sources. Existing methods typically rely on a preselected window size that determines their operating timescale, limiting their capacity to handle multi-scale sources. To address this issue, we …

abstract arxiv astro-ph.ep autoencoders cs.lg dataset knowledge martian prior scale series set signal stat.ml through type unsupervised variational autoencoders