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Questions tagged [probabilistic-programming]

19 questions with no upvoted or accepted answers
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6
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0answers
408 views

Comparing Factorie and Figaro languages for Statistical Relational Learning

I am looking to implement statistical relational learning, preferably in a modern programming language, and came across Factorie and Figaro for Scala. But most resources online that compare these are ...
5
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0answers
828 views

Probability distribution over classes as labels in classification task

Classical classification problem has next formulation. Given a set of $n$ attributes, a set of $k$ classes and a set of labelled training instances: $(i_i, l_j),...,(i_j, l_j)$, where $ i = (v_1, v_2,...
4
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0answers
65 views

Predicting a Twitter user from individual tweets probabilities

Let's say I have three tweets and those three tweets are all from either Mary or John. There is no possibility for mixed result. ...
4
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2answers
48 views

Using Bayesian Graphical Models to reconstruct duplicated damaged data

I am a computer science student specialised in machine learning. Recently I fell in love with Probabilistic Graphical Models (and probabilistic programming) because of the flexibility to focus on ...
3
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0answers
450 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
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0answers
29 views

How to get quantiles/probabilities of time series forecasts?

my problem is as follows : I am creating demand forecasts for some goods with different methods (ARIMA, ETS,..) The issue is that I would like to forecast the probabilities of those forecasts since ...
1
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0answers
282 views

How Deep Probabilistic (Graphical) Models differs from the usual Probabilistic Graphical Models?

How Deep Probabilistic (Graphical) Models differs from the usual Probabilistic Graphical Models? What are the main applications and state of art results of Deep Probabilistic Models?
1
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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 ...
1
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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. ...
1
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1answer
55 views

Switchpoint test with many customers

Im just reading the wunderful book Probabilistic Programming and Bayesian Methods for Hackers. In the very first chapter they inspect whether the habits of one single customer change over time, for ...
1
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0answers
55 views

What data generating process can't be expressed as a probabilistic graphical model?

I've been reading a bit on probabilistic programming, and one of the main claims is that it is more expressive than graphical models. As the representational capacity of PPLs is anything that can be ...
1
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0answers
146 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.
1
vote
1answer
107 views

Need direction in regards to probability based random value generation

I have a daily stream discharge data set spanning 10 years whose histogram looks like this: I would like to use it to set the distribution for a randomly chosen discharge for a given timestep. That ...
1
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0answers
172 views

Bound on the expectancy of the maximum level in skip list

Let $M$ be a random variable for the maximum level of skip list, $M$ is a positive integer, $k$ is an integer from 0 to $\infty$, and $$ \Pr(M>k) = 1 - (1-p^k)^n \leq np^k $$ In the article Skip ...
0
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0answers
11 views

Time series - probabilistic graph model

I am very new to Graph models, this is my first attempt. I have good knowledge of time series analysis. I am looking to build a graph model for a set of time series data - daily stock prices for say ...
0
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1answer
104 views

MAP of Gaussian Process Classification in Tensorflow Probability

I'm attempting to implement Gaussian Process Classification learning in tensorflow-probability, but my estimator turns out to be very biased toward zero. As opposed ...
0
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0answers
26 views

finding the 'best' set

I came across this simple looking but puzzling question recently. There is a set of N tuples given [(a1,b1), ..., (aN, bN)], where a are real numbers and b are positive real numbers. We need to choose ...
0
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0answers
26 views

Unbiasedness of confounding variable models

This is a question based on work in this paper: https://dl4physicalsciences.github.io/files/nips_dlps_2017_14.pdf I am interested in causality and representations using probabilistic graphical ...
0
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2answers
233 views

Is it possible to model using Bayesian Network (probabilistic graphical model) if you have no prior knowledge of the data?

Is it possible to model using Bayesian Network (probabilistic graphical model) if you have no idea at all of the interaction of the variables in the data? From my reading, I find that Bayesian network ...