# Questions tagged [probabilistic-programming]

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### Is it possible to train probabilistic model to return several distributions?

I have nonlinear data of function y(x), which is let's say parabolic. At some points of x there are several y's (look at the picture). Is it possible to train a probabilistic model to return several ...
• 141
412 views

### Layman's description of PDF and CDF [closed]

Can anyone please explain what a PDF and CDF are in simple words. (Please don't define it from wiki.)
• 21
1 vote
623 views

### What's the difference between probabilistic programming such as pyro and belief networks?

I heard about ubers pyro and stumbled upon this Wikipedia article. As I understand, a bayesian network is the same as a belief network according to this post. Does someone know how these are related?...
1 vote
93 views

### the probability distribution of dependent variables

There are three variables, X3 is a function of X1 and X2, ...
• 253
1 vote
964 views

### How to generate a sample from a generative model like a Restricted Boltzmann Machine?

I am learning about the Boltzmann machine. So far, I have successfully written a code that can learn the coefficients of the energy function of a Restricted Boltzmann Machine. Now, since my model is ...
• 175
1 vote
2k views

### PyMC3 do not converge

I'm trying to run a simple logistic regression on PyMC3. Here the code: ...
• 1,754
1 vote
99 views

### How to interpret a Bayesian neural network prediction for binary classification in comparison to deterministic neural network?

Allow me to clarify my current understanding: Interpreting a binary classification prediction made by a deterministic neural network On one hand, point estimates fall on a sigmoid curve (between 0-1, ...
• 519
1 vote
45 views

### Bayes posteriograms

My main objective is to predict the posterior probability of an individual belonging to one of the classes, using Bayes theorem. The information I have is: value of the data point mean and stdev of ...
1 vote
1k views

### Bayes net inference in Pyro

I am familiar with Bayes nets (discrete/continuous/hybrid). I recently started to learn basics of Pyro and tried to model simple Bayes nets as Pyro programs. I also noticed the simple example answered ...
• 56
1 vote
294 views

### Laplacian smoothing on Class Probability (Naive bayes)

I am implementing a Naive Bayes classifier in Python from scratch. The instructions I have asks that I incorporate Laplacian Smoothing with K=1 to computing the probability that a message belongs to a ...