Exploring Neural Granger Causality with xLSTMs: Unveiling Temporal Dependencies in Complex Data
–Neural Information Processing Systems
Causality in time series can be challenging to determine, especially in the presence of non-linear dependencies. Granger causality helps analyze potential relationships between variables, thereby offering a method to determine whether one time series can predict--Granger cause--future values of another.
Neural Information Processing Systems
Jun-15-2026, 08:57:41 GMT
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