Available models

Model	Local/global	Data layout	Architecture/method	Implementation
DeepAR [Salinas et al. 2020]	Global	Univariate	RNN	MXNet, PyTorch
DeepState [Rangapuram et al. 2018]	Global	Univariate	RNN, state-space model	MXNet
DeepFactor [Wang et al. 2019]	Global	Univariate	RNN, state-space model, Gaussian process	MXNet
Deep Renewal Processes [Türkmen et al. 2021]	Global	Univariate	RNN	MXNet
GPForecaster	Global	Univariate	MLP, Gaussian process	MXNet
MQ-CNN [Wen et al. 2017]	Global	Univariate	CNN encoder, MLP decoder	MXNet
MQ-RNN [Wen et al. 2017]	Global	Univariate	RNN encoder, MLP encoder	MXNet
N-BEATS [Oreshkin et al. 2019]	Global	Univariate	MLP, residual links	MXNet
Rotbaum [Hasson et al. 2021]	Global	Univariate	XGBoost, Quantile Regression Forests, LightGBM, Level Set Forecaster	Numpy
Causal Convolutional Transformer [Li et al. 2019]	Global	Univariate	Causal convolution, self attention	MXNet
Temporal Fusion Transformer [Lim et al. 2021]	Global	Univariate	LSTM, self attention	MXNet
Transformer [Vaswani et al. 2017]	Global	Univariate	MLP, multi-head attention	MXNet
WaveNet [van den Oord et al. 2016]	Global	Univariate	Dilated convolution	MXNet
SimpleFeedForward	Global	Univariate	MLP	MXNet, PyTorch
DeepVAR [Salinas et al. 2019]	Global	Multivariate	RNN	MXNet
GPVAR [Salinas et al. 2019]	Global	Multivariate	RNN, Gaussian process	MXNet
LSTNet [Lai et al. 2018]	Global	Multivariate	LSTM	MXNet
DeepTPP [Shchur et al. 2020]	Global	Multivariate events	RNN, temporal point process	MXNet
RForecast [Hyndman et al. 2008]	Local	Univariate	ARIMA, ETS, Croston, TBATS	Wrapped R package
Prophet [Taylor et al. 2017]	Local	Univariate	-	Wrapped Python package
NaiveSeasonal [Hyndman et al. 2018]	Local	Univariate	-	Numpy
Naive2 [Makridakis et al. 1998]	Local	Univariate	-	Numpy
NPTS	Local	Univariate	-	Numpy