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Found 4 papers, 3 papers with code
Leveraging Pre-Trained Autoencoders for Interpretable Prototype Learning of Music Audio
APNet allows prototypes' reconstruction to waveforms for interpretability relying on the nearest training data samples.
mir_ref: A Representation Evaluation Framework for Music Information Retrieval Tasks
Music Information Retrieval (MIR) research is increasingly leveraging representation learning to obtain more compact, powerful music audio representations for various downstream MIR tasks.
Multilabel Prototype Generation for Data Reduction in k-Nearest Neighbour classification
Prototype Generation (PG) methods are typically considered for improving the efficiency of the $k$-Nearest Neighbour ($k$NN) classifier when tackling high-size corpora.
TensorFlow Audio Models in Essentia
Essentia is a reference open-source C++/Python library for audio and music analysis.
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