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Towards Explainable Sequential Learning
Giacomo Bergami, Emma Packer, Kirsty Scott, Silvia Del Din
https://arxiv.org/abs/2505.23624 https://

Towards Explainable Sequential Learning
This paper offers a hybrid explainable temporal data processing pipeline, DataFul Explainable MultivariatE coRrelatIonal Temporal Artificial inTElligence (EMeriTAte+DF), bridging numerical-driven temporal data classification with an event-based one through verified artificial intelligence principles, enabling human-explainable results. This was possible through a preliminary a posteriori explainable phase describing the numerical input data in terms of concurrent constituents with numerical pay…