Model Overview

List of Models supported in pytorch-forecasting. See below the supported models separated by the version they are present in

v1 Models

This is the list of models that are present in the stable version of the pytorch-forecasting v1 and can be used in production

Name	Authors	Covariates	Multiple targets	Regression	Classification	Probabilistic	Prediction intervals	Flexible History Length	Cold Start	Compute (1-5)
DecoderMLP	jdb78	x	x	x	x	x	x	x	x	1
DeepAR	jdb78	x	x	x		x	x	x		3
NBeatsKAN	Sohaib-Ahmed21			x						1
NBeats	jdb78			x						1
NHiTS	jdb78	x	x	x		x	x			1
RecurrentNetwork	jdb78	x	x	x			x	x	x	2
TemporalFusionTransformer	jdb78	x	x	x	x	x	x	x	x	4
TiDEModel	Sohaib-Ahmed21	x	x	x			x	x		3
TimeXer	PranavBhatP	x	x	x			x	x		3
xLSTMTime	muslehal, phoeenniixx	x	x	x				x		3

v2 Models

The models that are present in the experimental, unstable pytorch-forecasting v2. These models should be used with CAUTION!

Name	Compatible Data Modules	Authors	Covariates	Multiple targets	Regression	Classification	Probabilistic	Prediction intervals	Flexible History Length	Cold Start	Compute (1-5)
DLinear_v2	TslibDataModule	PranavBhatP	x	x	x			x	x		2
Samformer_v2	EncoderDecoderTimeSeriesDataModule	fbk_dsipts, PranavBhatP	x		x			x			2
TFT_v2	EncoderDecoderTimeSeriesDataModule	phoeenniixx	x	x	x			x			3
TIDE_v2	EncoderDecoderTimeSeriesDataModule	fbk_dsipts, phoeenniixx	x	x	x						3
TimeXer_v2	TslibDataModule	PranavBhatP	x	x	x			x			3