models

Models for timeseries forecasting.

Modules

base	Base classes for pytorch-foercasting models.
base_model	Base classes for pytorch-foercasting models.
baseline	Baseline model.
deepar	DeepAR: Probabilistic forecasting with autoregressive recurrent networks.
dlinear	Decomposition-Linear model for time series forecasting.
mlp	Simple models based on fully connected networks.
nbeats	N-Beats model for timeseries forecasting without covariates.
nhits	N-HiTS model for timeseries forecasting with covariates.
nn
rnn	Simple recurrent model - either with LSTM or GRU cells.
samformer	DSIPTS Implementation of Samformer for V2 :2: (WARNING/2) Title underline too short. DSIPTS Implementation of Samformer for V2 --------------------------------------
temporal_fusion_transformer	Temporal fusion transformer for forecasting timeseries.
tide	Tide model.
timexer	TimeXer model for forecasting time series.
xlstm	xLSTMTime implementation for forecasting.