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  2. Restricted Boltzmann machine - Wikipedia

    en.wikipedia.org/wiki/Restricted_Boltzmann_machine

    A restricted Boltzmann machine (RBM) (also called a restricted Sherrington–Kirkpatrick model with external field or restricted stochastic Ising–Lenz–Little model) is a generative stochastic artificial neural network that can learn a probability distribution over its set of inputs.

  3. Vanishing gradient problem - Wikipedia

    en.wikipedia.org/wiki/Vanishing_gradient_problem

    It uses a restricted Boltzmann machine to model each new layer of higher level features. Each new layer guarantees an increase on the lower-bound of the log likelihood of the data, thus improving the model, if trained properly.

  4. Boltzmann machine - Wikipedia

    en.wikipedia.org/wiki/Boltzmann_machine

    This is not a restricted Boltzmann machine. A Boltzmann machine (also called Sherrington–Kirkpatrick model with external field or stochastic Ising model), named after Ludwig Boltzmann is a spin-glass model with an external field, i.e., a Sherrington–Kirkpatrick model, [1] that is a stochastic Ising model.

  5. Feature learning - Wikipedia

    en.wikipedia.org/wiki/Feature_learning

    Restricted Boltzmann machines (RBMs) are often used as a building block for multilayer learning architectures. [6] [24] An RBM can be represented by an undirected bipartite graph consisting of a group of binary hidden variables, a group of visible variables, and edges connecting the hidden and visible nodes.

  6. Types of artificial neural networks - Wikipedia

    en.wikipedia.org/wiki/Types_of_artificial_neural...

    The Boltzmann machine can be thought of as a noisy Hopfield network. It is one of the first neural networks to demonstrate learning of latent variables (hidden units). Boltzmann machine learning was at first slow to simulate, but the contrastive divergence algorithm speeds up training for Boltzmann machines and Products of Experts.

  7. Convolutional deep belief network - Wikipedia

    en.wikipedia.org/wiki/Convolutional_deep_belief...

    In computer science, a convolutional deep belief network (CDBN) is a type of deep artificial neural network composed of multiple layers of convolutional restricted Boltzmann machines stacked together. [1]

  8. Graphical model - Wikipedia

    en.wikipedia.org/wiki/Graphical_model

    A restricted Boltzmann machine is a bipartite generative model specified over an undirected graph. Applications. The framework of the models, ...

  9. Deep belief network - Wikipedia

    en.wikipedia.org/wiki/Deep_belief_network

    In machine learning, a deep belief network (DBN) is a generative graphical model, or alternatively a class of deep neural network, composed of multiple layers of latent variables ("hidden units"), with connections between the layers but not between units within each layer.