Comments (3)
pennfranc
commented on August 19, 2024
This indeed looks like a very cool possibility, thanks for putting this on our radar! This could be a subclass of our TorchForecastingModel class. If you're up for the challenge, you can always consider giving this a shot yourself too (check out this post for guidelines regarding implementing a new model). For now we will put this on our backlog.
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inverniz
commented on August 19, 2024
This seems interesting to me as well! I am currently giving it a try (still working on it locally). I will let you know how it goes!
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LeoTafti
commented on August 19, 2024
Will be part of the next release!
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Related Issues (20)
- Does Darts provide methods for unsupervised anomaly detection models? HOT 5
- FFT 2d forecasting HOT 1
- [Question] Are features scaled when using add_encoders? HOT 2
- [New Model] Pre-trained, "foundational" models HOT 2
- hyperparameter TiDE and TFT no complete trials HOT 3
- [Question] Is it possible to override the models' data loading methods? HOT 4
- Saving/loading model with a checkpoint callback HOT 2
- [BUG] TimeSeries should support the fill_missing_dates=False without freq HOT 1
- [BUG] Error when loading a saved TFTModel checkpoint HOT 2
- What is the difference between variable importance for the encoder and decoder in TFTExplainer? HOT 1
- Rolling prediction ；validation model HOT 1
- Tsmixer incorrect loss_fn/likelihood documentation HOT 1
- [BUG] darts should provide way to input multiprocessing_context parameter for dataloader when fit HOT 3
- [BUG] darts should support re-training base on the old checkpoint, not reset the model HOT 2
- Add KAN (Kolmogorov-Arnold Network) to Darts HOT 5
- Gridlines automatically created in matplotlib and seaborn plots [BUG] HOT 3
- How to mask or ignore target features during model training HOT 13
- Quantile forecasts are identical for all forecast horizons (XGBoost) HOT 2
- [BUG] TSMixer TimeBatchNorm2d using BatchNorm instead of LayerNorm HOT 6
- [BUG] Deterministic TFT model prediction not reproducable HOT 2
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