awesome-normalizing-flows VS PyMC

Compare awesome-normalizing-flows vs PyMC and see what are their differences.

awesome-normalizing-flows

Awesome resources on normalizing flows. (by janosh)
normalizing-flows bayesian-neural-networks variational-inference density-estimation generative-modeling autoregressive Machine Learning awesome-list bayesian-inference
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PyMC

Bayesian Modeling and Probabilistic Programming in Python (by pymc-devs)
Science and Data analysis Python statistical-analysis bayesian-inference Mcmc variational-inference probabilistic-programming pytensor
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docs.pymc.io
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awesome-normalizing-flows PyMC
1 3
1,313 8,202
- 1.2%
3.6 9.5
about 1 month ago 1 day ago
Python Python
MIT License GNU General Public License v3.0 or later
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

awesome-normalizing-flows

Posts with mentions or reviews of awesome-normalizing-flows. We have used some of these posts to build our list of alternatives and similar projects.
  • [D] Understanding Generative Flow
    1 project | /r/MachineLearning | 22 Jul 2021
    I would recommend this list of resources on github to get you started. In particular, I highly recommend this lecture by Marcus Brubaker et al which explains the essential components that you need: linear transformations, coupling layers and the multiscale architecture.

PyMC

Posts with mentions or reviews of PyMC. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-09-06.
  • PYMC Release: v5.0.0
    1 project | news.ycombinator.com | 12 Dec 2022
  • An Astronomer's Introduction to NumPyro
    1 project | news.ycombinator.com | 17 Aug 2022
    I believe the pymc versions were resolved into developing version 4 of pymc. Development at https://github.com/pymc-devs/pymc

    It still depends on theano now evolved and renamed

  • What is Probabilistic Programming?
    4 projects | /r/learnmachinelearning | 6 Sep 2021
    This tutorial explains what is probabilistic programming & provides a review of 5 frameworks (PPLs) using an example taken from Chapter 4 of Statistical Rethinking by Dr. Richard McElreath. Frameworks (PPLs) reviewed are - Stan (https://mc-stan.org/) PyMC3 (https://docs.pymc.io/) Tensorflow Probability (https://www.tensorflow.org/probability) Pyro/NumPyro (https://pyro.ai/) Turing.jl (https://turing.ml/stable/) I also provide the basic review of a great library called arviz (https://arviz-devs.github.io/arviz/), which can be used for all the above-mentioned PPLs to do Exploratory Data Analysis of Bayesian Models. Here is the link to the notebook in which I have implemented the example model using the above Frameworks/PPLs https://colab.research.google.com/drive/1zgR2b0j2waGi1ppnIe1rw7emkbBXtMqF?usp=sharing