7 votes
Accepted

Can Bayesian inference be combined with knowledge-based systems?

Yes, it is possible to combine probabilistic / bayesian reasoning and a traditional "knowledgebase". And some work along those lines has been done. See, for example, ProbLog ("Probabilistic Prolog") ...
mindcrime's user avatar
  • 3,757
1 vote

Why optimise log p(x) rather than log p(x|z) in a Variational AutoEncoder?

I thought $p(x)$ was just the distribution of $x$, which are the input variables we have observed. So how can we maximize $p(x)$, if it is the actual distribution of data in the real world? I think ...
Kostya's user avatar
  • 2,524
1 vote

Why optimise log p(x) rather than log p(x|z) in a Variational AutoEncoder?

TLDR: We're doing a maximum likelihood fit of our model. The VAE sets this up in a way that doesn't require evaluating the model likelihood, but instead expresses a lower bound in terms of ...
Luke's user avatar
  • 56
1 vote
Accepted

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

Using as a best reference accordingly my own google research, find the best post about best introductory Bayesian statistics book and summarize the answers. I find this post in stats.stackexchange ...
rubengavidia0x's user avatar

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