A general-purpose bioacoustic model from Google Deepmind, trained mostly on bird calls, consistently beats models specifically built to classify whale sounds. The reason traces back to evolutionary ...
Abstract: In many cases, observed brain signals can be assumed as the linear mixtures of unknown brain sources/components. It is the task of blind source separation (BSS) to find the sources. However, ...
scNym is a neural network model for predicting cell types from single cell profiling data (e.g. scRNA-seq) and deriving cell type representations from these models. While cell type classification is ...
Motor imagery (MI) allows the design of self-paced brain–computer interfaces (BCIs), which can potentially afford an intuitive and continuous interaction. However, the implementation of non-invasive ...
Ensemble classifiers have been proven to result in better classification accuracy than that of a single strong learner in many machine learning studies. Although many studies on electroencephalography ...
Welcome to the toolbox for tensor decompositions, statistical analysis, visualisation, feature extraction, regression and non-linear classification of multi-dimensional data. Not sure you need this ...
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