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View Code? Open in Web Editor NEWRestricted Boltzmann Machines (RBMs) in PyTorch
License: MIT License
Restricted Boltzmann Machines (RBMs) in PyTorch
License: MIT License
Hi Gabriel
Very helpful, I am looking to explore the use of an RBM in an autoencoder and this has saved me a lot of time.
One question, in the work I have seen where an RBM is trained using CD method, the readients are calculated using the visible and hidden states and not the probabilities. In this case this would mean that positive associations shouldbe the matric product of the input data and the positive_hidden_activations and not the positive_hidden_probabilities, which is what it is at present. The same would apply for the negative associations.
Is there a reason you have adopted this approach.
Once again thanks for this
John
Explain algorithm pls , i dont get it. This is RBM for real number, why you use Sigmoid ?
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