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Update Available Models (#2740)
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* Update TFT

* Update DeepNPTS and MQF2

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Co-authored-by: Abdul Fatir Ansari <ansarnd@amazon.com>
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abdulfatir and Abdul Fatir Ansari committed Mar 21, 2023
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10 changes: 8 additions & 2 deletions docs/getting_started/models.md
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Expand Up @@ -11,10 +11,12 @@ MQ-CNN<br>[Wen et al. 2017][Wen2017] | Global | Un
MQ-RNN<br>[Wen et al. 2017][Wen2017] | Global | Univariate | RNN encoder, MLP encoder | [MXNet][MQDNN]
N-BEATS<br>[Oreshkin et al. 2019][Oreshkin2019] | Global | Univariate | MLP, residual links | [MXNet][NBeats]
Rotbaum<br>[Hasson et al. 2021][Hasson2021] | Global | Univariate | XGBoost, Quantile Regression Forests, LightGBM, Level Set Forecaster | [Numpy][Rotbaum]
Temporal Fusion Transformer<br>[Lim et al. 2021][Lim2021] | Global | Univariate | LSTM, self attention | [MXNet][TFT]
Temporal Fusion Transformer<br>[Lim et al. 2021][Lim2021] | Global | Univariate | LSTM, self attention | [MXNet][TFT_mx], [PyTorch][TFT_torch]
Transformer<br>[Vaswani et al. 2017][Vaswani2017] | Global | Univariate | MLP, multi-head attention | [MXNet][Transformer]
WaveNet<br>[van den Oord et al. 2016][vanDenOord2016] | Global | Univariate | Dilated convolution | [MXNet][WaveNet]
SimpleFeedForward | Global | Univariate | MLP | [MXNet][SFF_mx], [PyTorch][SFF_torch]
DeepNPTS | Global | Univariate | MLP | [PyTorch][DeepNPTS_torch]
MQF2<br>[Kan et al. 2022][Kan2022] | Global | Univariate | RNN, ICNN | [PyTorch][MQF2_torch]
DeepVAR<br>[Salinas et al. 2019][Salinas2019] | Global | Multivariate | RNN | [MXNet][DeepVAR]
GPVAR<br>[Salinas et al. 2019][Salinas2019] | Global | Multivariate | RNN, Gaussian process | [MXNet][GPVAR]
LSTNet<br>[Lai et al. 2018][Lai2018] | Global | Multivariate | LSTM | [MXNet][LSTNet]
Expand All @@ -39,6 +41,7 @@ NPTS | Local | Un
[Lim2021]: https://doi.org/10.1016/j.ijforecast.2021.03.012
[Vaswani2017]: https://papers.nips.cc/paper/2017/hash/3f5ee243547dee91fbd053c1c4a845aa-Abstract.html
[vanDenOord2016]: https://arxiv.org/abs/1609.03499
[Kan2022]: https://arxiv.org/abs/2202.11316
[Salinas2019]: https://proceedings.neurips.cc/paper/2019/hash/0b105cf1504c4e241fcc6d519ea962fb-Abstract.html
[Lai2018]: https://doi.org/10.1145/3209978.3210006
[Shchur2020]: https://arxiv.org/pdf/1909.12127
Expand All @@ -58,11 +61,14 @@ NPTS | Local | Un
[MQDNN]: https://github.com/awslabs/gluonts/blob/dev/src/gluonts/mx/model/seq2seq/_mq_dnn_estimator.py
[NBeats]: https://github.com/awslabs/gluonts/blob/dev/src/gluonts/mx/model/n_beats/_estimator.py
[Rotbaum]: https://github.com/awslabs/gluonts/blob/dev/src/gluonts/ext/rotbaum/_estimator.py
[TFT]: https://github.com/awslabs/gluonts/blob/dev/src/gluonts/mx/model/tft/_estimator.py
[TFT_mx]: https://github.com/awslabs/gluonts/blob/dev/src/gluonts/mx/model/tft/_estimator.py
[TFT_torch]: https://github.com/awslabs/gluonts/blob/dev/src/gluonts/torch/model/tft/estimator.py
[Transformer]: https://github.com/awslabs/gluonts/blob/dev/src/gluonts/mx/model/transformer/_estimator.py
[WaveNet]: https://github.com/awslabs/gluonts/blob/dev/src/gluonts/mx/model/wavenet/_estimator.py
[SFF_mx]: https://github.com/awslabs/gluonts/blob/dev/src/gluonts/mx/model/simple_feedforward/_estimator.py
[SFF_torch]: https://github.com/awslabs/gluonts/blob/dev/src/gluonts/torch/model/simple_feedforward/estimator.py
[DeepNPTS_torch]: https://github.com/awslabs/gluonts/blob/dev/src/gluonts/torch/model/deep_npts/_estimator.py
[MQF2_torch]: https://github.com/awslabs/gluonts/blob/dev/src/gluonts/torch/model/mqf2/estimator.py
[DeepVAR]: https://github.com/awslabs/gluonts/blob/dev/src/gluonts/mx/model/deepvar/_estimator.py
[DeepVARHierarchical]: https://github.com/awslabs/gluonts/blob/dev/src/gluonts/mx/model/deepvar_hierarchical/_estimator.py
[GPVAR]: https://github.com/awslabs/gluonts/blob/dev/src/gluonts/mx/model/gpvar/_estimator.py
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