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cs.LG2025
PruneGCRN: Minimizing and explaining spatio-temporal problems through node pruning
Javier García-Sigüenza, Mirco Nanni, Faraón Llorens-Largo +1
This work addresses the challenge of using a deep learning model to prune graphs and the ability of this method to integrate explainability into spatio-temporal problems through a…
cs.LG2023
A Bag of Receptive Fields for Time Series Extrinsic Predictions
Francesco Spinnato, Riccardo Guidotti, Anna Monreale +1
High-dimensional time series data poses challenges due to its dynamic nature, varying lengths, and presence of missing values. This kind of data requires extensive preprocessing, l…