Multi-class Logistic Regression Class The logistic regression is fully described by a weight matrix :math:`W` and bias vector :math:`b`. Clas

Denoising Auto-Encoder class (dA) A denoising autoencoders tries to reconstruct the input from a corrupted version of it by projecting it fir

Pool Layer of a convolutional network

Restricted Boltzmann Machine (RBM)

Deep Belief Network A deep belief network is obtained by stacking several RBMs on top of each other. The hidden layer of the RBM at layer `i`

Multi-class Logistic Regression Class The logistic regression is fully described by a weight matrix :math:`W` and bias vector :math:`b`. Clas

Multi-Layer Perceptron Class A multilayer perceptron is a feedforward artificial neural network model that has one layer or more of hidden un

elman neural net model

Simple class to train an RNN-RBM from MIDI files and to generate sample sequences.

Stacked denoising auto-encoder class (SdA) A stacked denoising autoencoder model is obtained by stacking several dAs. The hidden layer of the

Contractive Auto-Encoder class (cA) The contractive autoencoder tries to reconstruct the input with an additional constraint on the latent s

Convenience wrapper for performing Hybrid Monte Carlo (HMC). It creates the symbolic graph for performing an HMC simulation (using `hmc_move`

class SdC, main class for deep-clustering network, constructed by stacking multiple dA2 layers. It is possilbe to initialize the network wi

This class implements DCN with EMC clustering model

This class implements DCN with K-means clustering model