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FEMDA: Robust classification with Flexible Discriminant Analysis in heterogeneous data. Flexible EM-Inspired Discriminant Analysis is a robust supervised classification algorithm that performs well in noisy and contaminated datasets.
FEMDA: Robust classification with Flexible Discriminant Analysis in heterogeneous data. Flexible EM-Inspired Discriminant Analysis is a robust supervised classification algorithm that performs well in noisy and contaminated datasets.
This is an open source library that can be used to autofocus telescopes. It uses a novel algorithm based on robust statistics. For a preprint, see https://arxiv.org/abs/2201.12466 .The library is currently used in Astro Photography tool (APT) https://www.astrophotography.app/
A new take on EEG sleep spindles detection exploiting a generative model (dynamic bayesian network) to characterize reoccurring dynamical regimes of single-channel EEG.
This library is an implementation of the algorithm described in Distributed Trajectory Estimation with Privacy and Communication Constraints: a Two-Stage Distributed Gauss-Seidel Approach.