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Why can Generative Adversarial Networks (GANs) learn any probability distribution function (pdf)?
Published:
This is somewhat a work in progress post… In this post, I will talk about the ability of GANs to learn a probability density function (pdf). A pdf is used to specify the probability of the random variable falling within a particular range of values. For example, consider the amount of euros/dollars you spend on groceries each month (random variable). For one individual, this will just be one value (e.g., 200 euros) but now consider the montly spending on groceries of all the individuals in the Netherlands. This can be summarized efficiently with a pdf (the red line):
A Very Simple Membership Inference Attack
Published:
20 March, 2022
Measuring and comparing predictive power of churn estimation methods
Published:
26th of June 2018
Training a neural network for image recognition.
Published:
Training a neural network for image recognition.
1st of February 2018
Scraping with R
Published:
16 October, 2017
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