vbmc
Variational Bayesian Monte Carlo (VBMC) algorithm for posterior and model inference in MATLAB (by acerbilab)
pyro
Deep universal probabilistic programming with Python and PyTorch (by pyro-ppl)
vbmc | pyro | |
---|---|---|
2 | 9 | |
211 | 8,388 | |
1.9% | 0.8% | |
2.8 | 8.4 | |
about 1 year ago | 4 days ago | |
MATLAB | Python | |
BSD 3-clause "New" or "Revised" License | Apache License 2.0 |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
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.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
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.
vbmc
Posts with mentions or reviews of vbmc.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-04-05.
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[R] New open-source Python software for sample-efficient Bayesian inference
Relevant papers about the underlying algorithm were published at NeurIPS in 2018 and 2020, but this is the first Python implementation (there was a MATLAB implementation); the port took us a while but it can finally be used for machine learning purposes
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New Python open-source software for sample-efficient Bayesian inference
The MATLAB implementation has been around for a while, and other research groups have applied it among other things for Bayesian parameter inference in:
pyro
Posts with mentions or reviews of pyro.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2024-01-11.
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Show HN: Designing Bridges with PyTorch
Mostly I use pytorch for statistical modeling https://pyro.ai . Under the hood that package uses a lot of Monte Carlo integration and variational methods (i.e. integration by optimization). It does support neural nets, but probably >80% of pyro users stick to simpler hierarchical Bayesian models.
- Pyro: The Universal, Probablistic Programming Language
- The Jupyter+Git problem is now solved
- Pyro: Deep universal probabilistic programming with Python and PyTorch
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Computational Bayesian Inference Techniques
Amortized Variational Inference (Like done in pyro.ai with neural networks)
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[P] torchegranate: a PyTorch rewrite of the pomegranate library for probabilistic modeling
Can you compare this to Pyro, which is also built on top of PyTorch?
- [Q] Updated book or review paper on MCMC methods
- Is anyone here working in uncertainty estimation in neural networks?
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[D] Do you train and deploy models using just one framework or multiple frameworks at work?
Using pyod, statmodels, scikit-learn, Tensorflow and pyro.ai (that is using PyTorch as backend). I always use the same framework for training and for production.