LSTM-SAE

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Pytorch Implementation of LSTM-SAE(Long Short Term Memory - Stacked AutoEncoder)

LSTM-SAE 최신버젼 다운로드

최종 버전 다운로드 (.zip)

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# LSTM-SAE
Pytorch Implementation of LSTM-SAE(Long Short Term Memory - Stacked AutoEncoder)

## Description of Repo.
- 저자의 keras 구현 실습 예제
- pytorch로 구현한 내 모델
- dacon 대회에 적용한 결과

## Article
[Unsupervised Pre-training of a Deep LSTM-based Stacked Autoencoder for Multivariate Time Series Forecasting Problems](https://www.nature.com/articles/s41598-019-55320-6#Ack1) - nature

- **LSTM**

![img](https://media.springernature.com/full/springer-static/image/art%3A10.1038%2Fs41598-019-55320-6/MediaObjects/41598_2019_55320_Fig1_HTML.png?as=webp)

- **LSTM-AE**

![img](https://media.springernature.com/full/springer-static/image/art%3A10.1038%2Fs41598-019-55320-6/MediaObjects/41598_2019_55320_Fig3_HTML.png?as=webp)

- **LSTM-Stacked AutoEncoder**

![img](https://media.springernature.com/full/springer-static/image/art%3A10.1038%2Fs41598-019-55320-6/MediaObjects/41598_2019_55320_Fig4_HTML.png?as=webp)

## Reference
  - [L1aoXingyu/pytorch-beginner](https://github.com/L1aoXingyu/pytorch-beginner/blob/master/08-AutoEncoder/simple_autoencoder.py)
  - [Use of nn.Embedding for floating type numbers](https://discuss.pytorch.org/t/use-of-nn-embedding-for-floating-type-numbers/59205)
  - [How to correctly give inputs to Embedding, LSTM and Linear Layers?](https://discuss.pytorch.org/t/how-to-correctly-give-inputs-to-embedding-lstm-and-linear-layers/15398)
  - [LSTM Tutorial](https://pozalabs.github.io/lstm/)
  - [jinmang2/ELMo/char_cnn.py](https://github.com/jinmang2/ELMo/blob/master/elmo/modules/char_cnn.py)
  - [Convolution 1d and simple function](https://discuss.pytorch.org/t/convolution-1d-and-simple-function/11606/9)
  - [torch.nn](https://pytorch.org/docs/master/nn.html?highlight=lstm#torch.nn.LSTM)
  - [How to initialize weights in PyTorch?](https://stackoverflow.com/questions/49433936/how-to-initialize-weights-in-pytorch)
  - [How to initialize weights/bias of RNN LSTM GRU?](https://discuss.pytorch.org/t/how-to-initialize-weights-bias-of-rnn-lstm-gru/2879/7)
  - [Learn initial hidden state (h0) for RNN](https://discuss.pytorch.org/t/learn-initial-hidden-state-h0-for-rnn/10013/7)
  - [bentrevett/pytorch-seq2seq](https://github.com/bentrevett/pytorch-seq2seq)
  - [jinmang2/NPLM/nplm.py](https://github.com/jinmang2/NPLM/blob/master/nplm.py)

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