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Testing usefulness of convolution layers as part of a recurrent neural network

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convolution_experiments

Testing usefulness of convolution layers as part of a recurrent neural network

model_1.py -- Script uses a distance function from 2 boundary points (the zero level-set) in a 1-dimensional array, changing over time as training data. The in channels of the convolution are used as an alternative to a state vector to retain history information.

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Testing usefulness of convolution layers as part of a recurrent neural network

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