# Questions tagged [restricted-boltzmann-machine]

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

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### Energy function of a RBM

My question is simply why the Energy function of a RBM is given by: $$E = -\sum_{i,j} w_{ij} \, v_i \, h_j -\sum_i \alpha_i \, v_i - \sum_i \beta_i \, h_i$$ when the energy of the Boltzmann Machine is ...
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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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### Boltzmann machine method of evolution

When a Boltzmann machine modeling binary data 'evolves' to a lower energy state, does it typically evolve via the hebbian update rule (like hopfield nets), or gradient descent? My understanding is ...
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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 ...
1 vote
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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. ...
1 vote
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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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