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PyTorch Dual-Attention LSTM-Autoencoder For Multivariate Time Series

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Hi, As I understand well you create y_hist in order to perform training using teacher forcing by providing the true target value to the Decoder. As an argument to the...

bug
good first issue

Hi, nice project. Thanks for sharing. I am looking around and testing. It seems get_loaders function does not fit run_reconstruction. In particular the following line: `X_train, X_test, y_train, y_test =...

good first issue
invalid

The model worked fine for Netflix ticker but when I run for some other ticker, the model doesn't seem to learn. Or it learns with large errors. Can you try...

invalid

AssertionError if prediction window > 1. torch==1.4.0 ```` Traceback (most recent call last): File "", line 107, in run(vars(args)) File "", line 90, in run train_iter, test_iter, nb_features = ts.get_loaders(batch_size=config["batch_size"])...

invalid

Hello, I have a question. Can this code be used to perform prediction with 8 features and 3 outputs, where each output depends on the 8 features

question

Bumps [pillow](https://github.com/python-pillow/Pillow) from 9.2.0 to 10.0.1. Release notes Sourced from pillow's releases. 10.0.1 https://pillow.readthedocs.io/en/stable/releasenotes/10.0.1.html Changes Updated libwebp to 1.3.2 #7395 [@​radarhere] Updated zlib to 1.3 #7344 [@​radarhere] 10.0.0 https://pillow.readthedocs.io/en/stable/releasenotes/10.0.0.html Changes...

dependencies

Thanks for sharing the code, i learned a lot from it. I see that in eval.py evaluation is performed on the target scaled with StandardScaler I think that evaluation will...

I get error when the output_size isn't equal to 1 in forecasting code. for example when the output_size is 10. I get this error : return F.linear(input, self.weight, self.bias) RuntimeError:...

When I evaluate the model during training, it get a decent reconstruction result and loss value finally. But when I use the same data set to test the trained model,...

Hello, I am interested in using your code to remove noise from a set of time series (reconstruction). I would like to confirm the following: the series are divided (in...