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1answer
24 views

applied papers on probabilistic generative models and inference engines

I am looking for applications papers where people choose some task on which they will do Bayesian inferencing and graphical modeling, and then build an inference engine to infer latent parameters. And ...
7
votes
2answers
1k views

Probabilistic programming vs “traditional” ML

I was browsing the github repo for Pymc and found this notebook: Variational Inference: Bayesian Neural Networks The author extols the virtues of bayesian/probabilistic programming but then goes on ...
1
vote
0answers
27 views

“Blocking” effects in probabilistic programs

I'm trying to estimate a regression where: I can only see the sex of a subset of the population I do know the total population size I'd like to know how many events are driven my men vs women, using ...
0
votes
1answer
341 views

ADVI Best Practices

I tried replicating the stochastic vol example in the pymc3 documentation, but using a larger dataset. NUTS was taking too long, so I tried ADVI. ...
3
votes
0answers
409 views

Is probabilistic modeling the same thing as Bayesian modeling?

When titles, books, and posts refer to probabilistic modeling, coupled with it I usually see the word "Bayesian" near by and all around. If we were to think of this as a ven diagram, are they the same ...
1
vote
0answers
52 views

Bayesian/Probabilistic Programming with PyMC: Am I doing this right?

I've been playing around with Bayesian / Probabilistic Programming with PyMC and others. I can't find a ton of great practical examples on the web so I created my own problem and tried to solve it. ...
2
votes
1answer
250 views

Calculating acceptance rate in Monte Carlo Markov Chain while doing Bayesian analyis

I am doing Bayesian analysis using a Monte Carlo Markov Chain of length 10000 and burn-in length 1000. I consider my chain as converged when the acceptance rate is equal to 23% and the chain mixing ...
5
votes
1answer
2k views

PyMC3 Implementation of Probabilistic Matrix Factorization (PMF): MAP produces all 0s

I've started working with pymc3 over the past few days, and after getting a feel for the basics, I've tried implementing the Probabilistic Matrix Factorization model. For validation, I use a subset ...
1
vote
0answers
140 views

How to calculate the posterior probabilty of Gaussian Mixture Component

If the mean vector and the Covariance matrix of a Gaussian Mixture model are known, how could I calculate the posterior probability of each of the Gaussian Component in the mixture.
2
votes
1answer
686 views

Posterior autocorrelation in Pymc. How to interpret it?

I started learning Bayesian inference by reading "Probabilistic Programming and Bayesian Methods for Hackers". I found something that is not really clear for me in the third chapter. Lets look at the ...
3
votes
1answer
1k views

Why does my posterior distribution have probability values greater than 1? [duplicate]

I'm attempting to learn Bayesian modelling with PyMC, so I have been going through Cam Pilon Davidson's Probabilistic Programming for Hackers. I literally copied his code from chapter 1 and used my ...
8
votes
1answer
603 views

Hierarchical Bayesian modeling of incidence rates

Kevin Murphy's book discusses a classical Hierarchical Bayesian problem (originally discussed in Johnson and Albert, 1999, p24): Suppose that we are trying to ...