spdlearn/spd_learn
SPDlearn: A Geometric Deep Learning Python Library for Neural Decoding Through Trivialization
SPDlearn helps researchers and engineers working with biological signals, like EEG, to build and train advanced deep learning models. It takes raw brain signal data, processes it into special mathematical matrices (Symmetric Positive Definite matrices), and uses these to train neural networks that can classify brain states or decode intentions for applications like Brain-Computer Interfaces. The primary users are neuroscientists, biomedical engineers, and machine learning researchers specializing in signal processing.
Use this if you are developing deep learning models for classifying or analyzing biological signals, particularly when these signals can be represented as Symmetric Positive Definite (SPD) matrices.
Not ideal if your data is not naturally represented as Symmetric Positive Definite matrices or if you are not working with Python and PyTorch.
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Python
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Last pushed
Mar 10, 2026
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