Questions tagged [bayesian-statistics]

For questions related to Bayesian statistics in the context of artificial intelligence. Bayesian statistics is a system for describing uncertainty using the mathematical language of probability. Bayesian statistical methods start with existing "prior" beliefs, and update these using data to give "posterior" beliefs.

See http://www.scholarpedia.org/article/Bayesian_statistics for more info.

6 questions

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2 answers

Are Bayesian networks important to learn in 2018?

I study AI by myself with the book "Artificial Intelligence: A Modern Approach". I've just finished the chapters about the Bayesian network and probabilities, and I found them very interesting. Now, I want to implement different algorithms and test…

bayesian-networks bayesian-statistics

asked May 29 '18 at 19:30

kaizokun

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1 answer

What does the notation $\mathcal{N}(z; \mu, \sigma)$ stand for in statistics?

I know that the notation $\mathcal{N}(\mu, \sigma)$ stands for a normal distribution. But I'm reading the book "An Introduction to Variational Autoencoders" and in it, there is this notation: $$\mathcal{N}(z; 0, I)$$ What does it mean? picture of…

terminology variational-autoencoder notation random-variable bayesian-statistics

asked Aug 23 '20 at 17:49

Peyman

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1 answer

Why do Bayesian algorithms work well with small datasets?

I read very often that Bayesian algorithms work well on small datasets. Why is that? I think it is because they might generalize more, but why is that? See also Investigating the use of Bayesian networks for small dataset problems.

machine-learning bayesian-networks naive-bayes bayesian-statistics

asked Nov 23 '19 at 08:10

jennifer ruurs

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1 answer

Is there an entry level textbook on Bayesian Inference that is a nice blend of theory and applications?

I am looking for a textbook that is a nice entry level to Bayesian Inference. I was hoping that there is a nice blend of theory and applications (data sets) on how concepts are applied. Programming techniques presented are welcome. Just for…

reference-request books bayesian-statistics bayesian-inference

asked Aug 11 '21 at 09:52

cgo

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0 answers

Will adding memory to a supervised learning system makes it into a Bayesian learning system?

Seung et.al recently published GameGAN paper, GameGAN learned and stored the whole Pacman game and was able to reproduce it without a game engine. The uniqueness of GameGAN is that it had added memory to its discriminator/generator which helped it…

generative-adversarial-networks bayesian-deep-learning bayesian-statistics game-gan

asked Jun 13 '20 at 06:43

Eka

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8
23

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Thompson sampling with Bernoulli prior and non-binary reward update

I am solving a problem for which I have to select the best possible servers (level 1) to hit for a given data. These servers (level 1) in turn hit some other servers (level 2) to complete the request. The level 1 servers have the same set of level 2…

reinforcement-learning reward-design reward-functions bayesian-statistics thompson-sampling

asked Nov 16 '20 at 07:56

PUNEET AGARWAL