gammy VS awesome-normalizing-flows

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

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gammy awesome-normalizing-flows
2 1
75 1,306
- -
4.7 3.6
24 days ago 30 days ago
Python Python
MIT License MIT License
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.

gammy

Posts with mentions or reviews of gammy. We have used some of these posts to build our list of alternatives and similar projects.

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.

What are some alternatives?

When comparing gammy and awesome-normalizing-flows you can also consider the following projects:

PyMC - Bayesian Modeling and Probabilistic Programming in Python

nflows - Normalizing flows in PyTorch

autoregressive - :kiwi_fruit: Autoregressive Models in PyTorch.

InvertibleNetworks.jl - A Julia framework for invertible neural networks

vbmc - Variational Bayesian Monte Carlo (VBMC) algorithm for posterior and model inference in MATLAB

Tensorflow-iOS

pyro - Deep universal probabilistic programming with Python and PyTorch