[QUESTION] Have you considered more advanced outlier detection and value imputation?

Hi,

I am working with low-quality time series from low-quality sensors in cities, and the problem of detecting outliers and imputing values to obtain higher-quality time series is a major concern.

I’d like to know if you’ve considered this.

Here’s a model that I find very interesting: https://huggingface.co/ibm-granite/granite-timeseries-tspulse-r1