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Questions tagged [restricted-boltzmann-machine]

a Restricted Boltzmann Machine (RBM) is a kind of artificial neural network.

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Sampling Gauss-Bernoulli RBM

In the 2018 paper Stein Variational Gradient Descent Without Gradient the authors analyze the sampling performance of their algorithm on multiple benchmarks. One of them is sampling from a Gauss-...
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Notation for calculating $p(v)$ marginalising over $h$ in an Restricted Boltzmann Machine

I am working through equation 22 in Introduction to Boltzmann Machines I am a little confused with the notation, in particular in the line: As I understand it, we want the probability of a specific ...
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Restricted Boltzmann Machine: W matrix visualization results after training MNIST images and Pseudo-log-likelihood

I am implementing RBM from scratch using Tensorflow and after training my RBM on the MNIST dataset for 200 epochs using Persistent CD with two steps of contrastive divergence, I learn the weights W ...
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Restricted Boltzmann Machines vs GAN

Can someone please tell me how RBMs and GANs compare to each other? I know that the community is more excited over GANs than RBMs at the moment. I guess it's because GANs produce better results? My ...
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explanation of RBM definition

I'm learning about RBM and I try to understand the notation used for it. We have the input vector $v=(v_i)$ and the output vector $h=(h_j)$, a weight matrix $W=(W_{ij})$ and finally two bias vectors - ...
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Why do we want (Restricted) Boltzmann Machines to be stochastic?

Boltzmann machines are stochastic recurrent neural networks with a specific architecture, and they are interesting in several contexts. They are stochastic in the sense that the sampling procedure ...
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Do stacked RBM's have any benefits/advantages over CNN?

Do stacked RBM's have any benefits/advantages over CNN? If the concern is about face recognition.
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Why is MCMC not reliable when compared to stochastic gradient descent?

I came across the following quote on enter link description here if we made MCMC as reliable as stochastic gradient descent now is for deep networks, that could mean a resurgence of more explicit ...
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Restricted Boltzmann Machines - Understanding contrastive divergence vs. ML learning

I've read many articles about RBMs as well as Hinton's original paper about the CD algorithm (at least roughly), but I still don't get the big picture. I understand CD conceptually and I've already ...
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scikit's RBM pseudo likelihood calculation

According to scikit-learn's documentation given here, the pseudo likelihood is calculated by; Computing the free energy on X, then on a randomly corrupted version of X, and returns the log of the ...
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What does it mean to sample from an RBM?

In restricted Boltzmann machines we ofter say that given $v$ we sample $h$, and also that given $h$ we sample $v$. Can someone explain the physical meaning of this, considering a MNIST image as ...
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KL divergence derivation

I want to understand KL divergene. Can someone please explain why we need inequality lnx
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partition function therm in the derivation of log likelihood in RBM?

In the following derivation when we take derivative of second term why the summation is only over h although it should be be over v and h because we are dealing with Z.
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Conditional probability expression in restricted boltzmann machine? How to get p(h=1|v)?

I'm reading a book on Deep learning and having trouble in deriving an expression Can someone please explain how to go from equation(20.10) to (20.11)? How summation term is converting into product ...
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How does a hidden unit in a Boltzmann Machine differ from a hidden unit in a Neural Network?

I was reading about Boltzmann Machines, and I found this: The state of a hidden unit in a Boltzmann Machine is a random variable, but in a Neural Net it is a deterministic function of the inputs. ...
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Why is the log likelihood used for the loss function in an RBM

In an RBM, the loss function is defined like this: Why are we using the log likelihood function? How does that measure the error?
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What are fantasy particles in RBMs

In Restricted Boltzman Machines, when collecting the statistics I sometimes heard of fantasy particles being used. What are these? How are they useful?
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Understanding a simple example of restricted Boltzmann machine (RBM)

I am trying to get an intuitive idea of RBMs out of curiosity, and using a simple example on youtube based on preferences for different sports, which denote profiles roughly corresponding to ...
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Restricted Boltzmann Machine: how to implement Gaussian visible units

Please, I'm a newby with Restricted Boltzmann Machine, I'm a psychologist (not very good with math) and and I've some confusion about the use of Gaussian visible units. Note I'm working on the ...
2 votes
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Visible Layer Bias in Restricted Boltzmann Machines

In Neural Networks the bias term of the hidden units can be considered a threshold for the node to fire. This is how neurons basically work in the brain as well. In RBMs, also a bias for the visible ...
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ReLUs improve Restricted Boltzmann Machines

This question is about the use of Rectified Linear Units as hidden units in Restricted Boltzmann Machines. In Nair and Hinton's paper, using ReLUs as hidden units is proposed. In section 1, they ...
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