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cs.LG2023
Interpretable time series neural representation for classification purposes
Etienne Le Naour, Ghislain Agoua, Nicolas Baskiotis +1
Deep learning has made significant advances in creating efficient representations of time series data by automatically identifying complex patterns. However, these approaches lack…
cs.LG2021
Towards Rigorous Interpretations: a Formalisation of Feature Attribution
Darius Afchar, Romain Hennequin, Vincent Guigue
Feature attribution is often loosely presented as the process of selecting a subset of relevant features as a rationale of a prediction. Task-dependent by nature, precise definitio…