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Bayesian inference is a method of statistical inference that relies on treating the model parameters as random variables and applying Bayes' theorem to deduce subjective probability statements about the parameters or hypotheses, conditional on the observed dataset.

12 votes
2 answers
696 views

Why did Thomas Bayes find Bayes' theorem so challenging?

This is more of a history of science question, but I hope it's on-topic here. I've read that Thomas Bayes only managed to discover Bayes' theorem for the special case of a uniform prior, and even the …
MWB's user avatar
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5 votes
1 answer
866 views

Gaussian Process and Expectation Propagation time complexity?

What's the time complexity of training a Gaussian process and its Expectation Propagation approximation? (Before studying them, I'd like to understand if they are even feasible for my application)
MWB's user avatar
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31 votes
2 answers
11k views

Is it true that Bayesian methods don't overfit?

Is it true that Bayesian methods don't overfit? …
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