Comments (4)
Congratulations on the paper !
Kindly asking to make your code publicly available.
Many Thanks!
from ast.
@hihihihiwsf Many Thanks for sharing the code, very much appreciated!
In your paper, you also mention that you have a DeepAR extension equipped with adversarial training. Would it be possible to share this code also. Would be great!
from ast.
@hihihihiwsf Many Thanks for sharing the code, very much appreciated!
In your paper, you also mention that you have a DeepAR extension equipped with adversarial training. Would it be possible to share this code also. Would be great!
Hi, thanks for your interest. I reproduced DeepAR refering to https://github.com/zhykoties/TimeSeries. And only attached a Discriminator above the model, just like in AST.
from ast.
@hihihihiwsf I would greatly appreciate if you would be so kind to share the Adverserial DeepAR code, since this would facilitate reproducibility of your aproach. Would love to test the Adverserial DeepAR model.
Many thanks!
from ast.
Related Issues (10)
- The data set HOT 1
- Params.json example HOT 3
- preprocess_data.py reference
- Code to reproduce experiments
- requirement.txt
- how does the embed() work in gan_transformer.py? HOT 3
- How to update the q90? HOT 1
- There seems to be something wrong with function test() in gan_transformer.py ? HOT 2
- RuntimeError: The size of tensor a (160) must match the size of tensor b (24) at non-singleton dimension 2 HOT 1
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from ast.