# Questions tagged [generative-model]

For questions related to the concept of generative machine learning models, such as the Restricted Boltzmann Machine (RBM), the Variational Autoencoder (VAE), and the Generative Adversarial Network (GAN).

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### Is plain autoencoder a generative model?

I am wondering how a plain auto encoder is a generative model though its version might be but how can a plain auto encoder can be generative. I know that Vaes which is a version of the autoencoder is ...
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### What is the exact role of model $p_\theta$ in diffusion models for the reverse process?

I'm reading this interesting blog post explaining diffusion probabilistic models and trying to understand the following. In order to compute the reverse process, we need to consider the posterior ...
• 197
1 vote
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### How to generate new data given a trained VAE - sample from the learned latent space or from multivariate Gaussian?

To generate synthetic dataset using a trained VAE, there is confusion between two approaches: Use learned latent space: z = mu + (eps * log_var) to generate (...
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1 vote
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### Why don't we also need to approximate $p(x \mid z)$ in the VAE?

In the VAE, we approximate the probability distribution $p(z \mid x)$, where $z$ is the latent vector and $x$ is our data. The reason is that $p(z \mid x)$ becomes impossible to calculate for ...
1 vote
36 views

### Which formula of p(x, y) to use?

The probability distribution $p(x, y)$ can be calculated in two ways : $p(x, y) = p(y \mid x) p(x)$ $p(x, y) = p(x \mid y) p(y)$ But according to the book Deep Generative Modeling (page number 3 ...
38 views

### Why do we use the same parameters for the joint, marginal and conditional distributions in VAEs?

I've noticed in several resources on variational autoencoders (for example the wikipedia article), we use the same parameters theta for the prior, likelihood, posterior, etc distributions. For example ...
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1 vote
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### Why is it easier to construct adversarial examples relative to training neural networks?

I was having looking at this lecture by Ian Goodfellow and my doubt is around 18:00 timestamp where he explains generation of adversarial examples using FGSM. He mentions that the there is a linear ...
106 views

### Generating fake faces containing specific features with GANs

I'm trying to understand how DeepFakes are generated and so far I understood that they're mostly generated through the usage of GANs and autoencoders. The autoencoders part is understandable, but what ...
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1 vote
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### How does NN follows law of energy conservation?

Communication requires energy, and using energy requires communication. According to Shannon, the entropy value of a piece of information provides an absolute limit on the shortest possible average ...
98 views

### How to define loss function for Discriminator in GANs?

To train the discriminator network in GANs we set the label for the true samples as $1$ and $0$ for fake ones. Then we use binary cross-entropy loss for training. Since we set the label $1$ for true ...
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### What is the right way to train a generator in a GAN?

I am not fully understanding how to train a GAN's generator. I have a few questions below, but let me first describe what I am doing. I am using the MNIST dataset. I generate a batch of random images ...
1 vote
129 views

### Is it legal to license and sell the output of a neural network that was trained on data that you don't own the license to?

Is it legal to license and sell the output of a neural network that was trained on data that you don't own the license to? For example, suppose you trained WaveNet on a collection of popular music. ...
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1 vote
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### What is meant by degrees of freedom of latent variables?

...Designing such a likelihood function is typically challenging; however, we observe that features like spectrogram are effective when latent variables have limited degrees of freedom. This motivates ...
1 vote
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### Concrete example of how transposed convolutions are able to *add* features to an image

Say we have a simple gray scale image. If we use a filter which is just the 3x3 identity matrix (or more pointedly the identity matrix but with -1 instead of the 0 entries), it is fairly easy to see ...
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1 vote
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### Is GAIL applicable if the expert's trajectories are for the same task but are in a different environment?

Is the GAIL applicable if the expert's trajectories (sample data) are for the same task but are in a different environment (modified but will not be completely different)? My gut feeling is, yes, ...
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### How to combine several chatbots into one?

I'm in the middle of a project in which I want to generate a TV series script (characters answering to each other, scene by scene) using SOTA models, and I need some guidance to simplify my ...
1 vote
44 views

### How do I sample conditionally from deep belief networks?

Deep belief networks (DBNs) are generative models, where, usually, you sample by thermalising the deepest layer (as it's a restricted Boltzmann machine), and then forward propagating a sample towards ...
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