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TF implementation of Inception Time - optimized for each task using Grid Search #23
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add noise to test data to assess robustness
epoch = 2 for my model in order to test.
Add right config name
Save results from gridsearch to Google Drive (save each gridsearch round to ensure that results gets stored)
Hi @Bsingstad , first of all I have to excuse myself for the very (very) late reply on this PR! big sorry for that! Overall, your PR looks great, however I need to request some changes. In particular:
other than that, your PR looks great, I'm curious to do pull request once the issues are resolved. What do you think about our suggestions? Best, |
Hi @helme Thank you for your suggestions. I will address them as soon as I can. Best regards |
Hi @helme Sorry for taking so long time. I have now updated the pull request according to your requirements:
but we didn't find a way to only train the specific models without doing major changes in your base code. |
removed matplotlib and debugging stuff
did the changes according to my comments
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Hi, first of all, thank your very much for this PR, looks promising :)
However, I still request some changes such that the reproduction of the results is still possible. Could you do this?
Hi @Bsingstad, |
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I am satisfied with your change requests
I have now committed the changes based on your last review |
In this pull request, we propose a new implementation of Inception Time (Tensorflow) which parameters are optimized using grid search. This work will be further explained in a paper published in ReScience C journal : http://rescience.github.io/