madtoinou

Which sanity checking are you referring to?

Hi @Laenita, Is the problem still occurring? The sanity checks is a mechanism implemented by pytorch lightning (see [here](https://lightning.ai/docs/pytorch/stable/debug/debugging_basic.html#run-a-sanity-check)), you could try to disable it by passing `pl_trainer_kwargs={"num_sanity_val_steps":0}`. Since #2295...

Hi @flight505, In general, `NaN` in the forecasts and scores are caused by missing values in the `TimeSeries`. Can you verify if any of your series contain such values? Checking...

Hi @ETTAN93, At the moment, Darts does not offer any unsupervised models for anomaly detection but it can be added to the roadmap, especially if contributors propose architectures and open...

Hi @yunakkano, If you have a component that you're not interested in forecasting, you have two options: - use it as a covariate instead, from what you described, probably a...

Closing this issue, the feature request is covered by #2151 (and the code snippet shared are probably a good start to implement such a thing).

Hi @AlexLazarovich, If you come up with a nice way to flatten (and then reshape back) your matrix/image into `TimeSeries` components, it should be possible? However, due to considerable dimensions...

Hi @ALH84007, Your code looks great; you fit the `Scaler` on the training split of the target and then, apply it to the validation and test sets before concatenating them...

If the new covariates can be considered as new components, and not "temporal continuation" of existing components, you indeed need to stack them. The code will continue to work as...

Hi @eetulauri, This is on Darts' roadmap but we would like to add conformal prediction before tackling the classification features as it would require some work for the deep learning...