How to Invert a Neural Network
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I have trained a model with states as inputs and an output of the cumulative distribution function (CDF) of any specific state, which is designed to mitiage any confusion in the network if multiple points have the same probability. I would like to flip the model instead of training an entirely new model because of the computational requirements and the probability that they won't agree with each other. Does anyone know how to do this with Matlab's Deep Learning Toolbox?
Trained: CDF = NN(X)
Invert: X = NN(CDF)
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Taimoor Tariq
2020-2-3
Maybe this will help.
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Taimoor Tariq
2020-2-5
编辑:Taimoor Tariq
2020-2-5
The code is compatible with Image input CNNs defined using matconvnet. Now if you have a Image input model trained on the Deep Learning Toolbox, you could probably export it to matconvnet using ONNX and then use the code. However, I think in your case In dont think you are using images as input, you would probably have to tweak the code a lot, or maybe write your own.
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Srivardhan Gadila
2020-1-17
If your network is a fully connected, has no non-linearities(like activations)/non-linear layers and has invertible wieght matrices for all your layers, then only you can invert your trained network by using the inverted weight matrices & bias vectors.
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John D'Errico
2020-1-22
Note that any such inverse as you desire need not be unique, or even terribly well posed, just as would be true for any inverse of a general nonlinear relationship.
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