2 papers
stat.ML2026
Autorelevance function and other feature relevance measures for univariate time series
Julian Cardenas, Jamie Arjona, Pedro Delicado
We propose a model agnostic methodology to measure lag relevance in machine learning forecasting models applied to univariate time series. Particularly, we are working in the conte…
cs.LG2024
Synthetic ECG Generation for Data Augmentation and Transfer Learning in Arrhythmia Classification
José Fernando Núñez, Jamie Arjona, Javier Béjar
Deep learning models need a sufficient amount of data in order to be able to find the hidden patterns in it. It is the purpose of generative modeling to learn the data distribution…