An Introduction to Restricted Boltzmann Machines

@inproceedings{Fischer2012AnIT,
  title={An Introduction to Restricted Boltzmann Machines},
  author={Asja Fischer and C. Igel},
  booktitle={CIARP},
  year={2012}
}
  • Asja Fischer, C. Igel
  • Published in CIARP 2012
  • Computer Science
  • Restricted Boltzmann machines (RBMs) are probabilistic graphical models that can be interpreted as stochastic neural networks. [...] Key Method Different learning algorithms for RBMs are discussed. As most of them are based on Markov chain Monte Carlo (MCMC) methods, an introduction to Markov chains and the required MCMC techniques is provided.Expand Abstract
    Training restricted Boltzmann machines: An introduction
    • 288
    • Open Access
    Restricted Boltzmann Machines: Introduction and Review
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    Training Restricted Boltzmann Machines
    • 25
    • Open Access
    Temperature based Restricted Boltzmann Machines
    • 19
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    Geometry and expressive power of conditional restricted Boltzmann machines
    • 18
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    Expressive Power of Conditional Restricted Boltzmann Machines
    • 4
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    Improving mixing rate with tempered transition for learning restricted Boltzmann machines
    • 9
    TRAINING THROUGH ANNEALING
    Restricted Boltzmann Machines: an Eigencentrality-based Approach

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