Clarification on Data Scaling for Zero-Shot Time Series Predictions Using TimesFM

[mrlucasrib]

Hello,

I am working on time series predictions in a zero-shot setting and noticed that neither this model nor other time series foundation models seem to perform any scaling (e.g., standardization or normalization) on the dataset before running it through the model.

This raises a question:

Is scaling omitted because the models assume that users will handle it beforehand?
Or is scaling unnecessary for these models?
I would greatly appreciate any clarification or guidance regarding the appropriate preprocessing steps, particularly in the context of zero-shot predictions.

Additional Information:
I am using the GluonTS library with a class wrapper to run the model. For reference, here is the implementation I am working with:
TimesFM Notebook.

Thank you for your assistance!