google / google/data-driven-discretization-1d
Could you release the arguments used for generating all the datasets?
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I could not reproduce the training set you provide when I ran "create_training_data.py" with the default arguments. Is it possible to release the arguments you used for generating all training data and exact data?
And I found that the shape of the training data mismatches your description in the paper: "To train the network we generate a set of 8000 high-resolution solutions to each equation, sampled at regular time intervals from 800 numerical integrations." However, the provided training data of Burger's equation has a shape of [10000, 512] instead of [8000, 512]. Could you explain the difference here?
Since I want to make some modifications based on the equations used in this paper, I want to keep the same parameters for generating data.
Thanks!
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