Questions tagged [noise]
9 questions
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Connexion between noise and score in Diffusion models
I'm new to diffusion models so I'm trying to familiarize myself with the theory.
In the article Score-Based Generative Modeling through Stochastic Differential Equations (Song and al.), it's explained that we need to solve the reverse-time SDE to…
Pepper08
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Solving Highly Stochastic Environments Using Reinforcement Learning
I've been working on a reinforcement learning (RL) problem in a highly stochastic environment where the effect of the noise far outweighs the impact of the agent's actions. To illustrate, consider the following example:
$ s' = s + a + \epsilon…
PJORR
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What are all the inputs that support diversity of images in text to image generation?
For this question, consider the stable diffusion model.
For a given text embedding, Stable Diffusion can generate diverse images. In this context, 'diversity' refers to the variation among the images generated, meaning that several images with the…
hanugm
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Are diffusion models still beneficial in highly compressed latent spaces?
Consider for example the MNIST dataset. When we apply diffusion to the pixel space, the image slowly becomes more and more noisy until white noise has been reached (like below). In the last step (t=100), the image does not really depend on the…
Thomas Wagenaar
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What are the best practices of adding noise to game-playing bots?
I write bots that play card games. From time to time, I add noise to their decisions, mainly for two reasons:
Reduce predictability: In games with hidden information the optimal play is a mix between several actions.
Reduce strength: allows to…
Cohensius
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Can a GAN Produce Different Inception Scores with the Same Dataset and Noise?
If the dataset, shuffle, and noise are all kept the same, is it possible for the same GAN to give different Inception Scores each time?
odbhut.shei.chhele
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Is the noise term $\epsilon$ in $y=g(x) + \epsilon$ used to denote the model's imperfection to the real world?
In supervised machine learning, it is common to say that we learn a function of the form
$$y=g(x) + \epsilon.$$
Generally, $\epsilon$ is used to denote noise or, more precisely, any influence by latent variables such as measurement inaccuracies…
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How does noise samples from uniform distribution contribute to the diversity of generator output?
In a Generative Adversarial Network (GAN), there are two multi-layer perceptrons. One is the generator network and another is a discriminator network.
The input for the generator network is a noise vector $z$. The input for a discriminator network…
hanugm
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Why is noise vector represented by letter $z$?
Most of the notations in Artificial Intelligence are borrowed from the mathematics.
$x$ stands for input (vector), $y$ stands for output (vector) etc., and the list is long.
But, I am not sure whether $z$ has any (widely used) role in…
hanugm
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