Neural Basis Expansion Analysis for Interpretable Time Series Forecasting with Exogenous Variables (N-BEATSx)

Olivares et al. proposed an extension of the N-BEATS model by making it compatible with exogenous variables. The overall structure is the same (with blocks, stacks, and residual connections) as N-BEATS (Figure 16.1), so we will only be focusing on the key differences and additions that the N-BEATSx model puts forward.

Reference check

The research paper by Olivares et al. (N-BEATSx) is cited in the References section as 4.

Handling exogenous variables

In N-BEATS, the input to a block was the lookback window, . But here, the input to a block is both the lookback window, , and the array of exogenous variables, . These exogenous variables can be of two types: time-varying and static. The static variables are encoded using a static feature encoder. This is nothing but a single-layer FC that encodes the static information into a dimension specified by the user. Now, the...