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cs.CV2025
Time-aware UNet and super-resolution deep residual networks for spatial downscaling
Mika Sipilä, Sabrina Maggio, Sandra De Iaco +3
Satellite data of atmospheric pollutants are often available only at coarse spatial resolution, limiting their applicability in local-scale environmental analysis and decision-maki…
stat.ME2025
Independent vector analysis -- an introduction for statisticians
Miro Arvila, Klaus Nordhausen, Mika Sipilä +1
Blind source separation (BSS), particularly independent component analysis (ICA), has been widely used in various fields of science such as biomedical signal processing to recover…
stat.ML2025
Identifiable Autoregressive Variational Autoencoders for Nonlinear and Nonstationary Spatio-Temporal Blind Source Separation
Mika Sipilä, Klaus Nordhausen, Sara Taskinen
The modeling and prediction of multivariate spatio-temporal data involve numerous challenges. Dimension reduction methods can significantly simplify this process, provided that the…