Blackjax Alternatives

Similar projects and alternatives to blackjax based on common topics and language

bayeux

1 96 7.8 Python blackjax VS bayeux

State of the art inference for your bayesian models.
pyro

9 8,364 8.4 Python blackjax VS pyro

Deep universal probabilistic programming with Python and PyTorch
InfluxDB

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Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
PyMC

3 8,155 9.5 Python blackjax VS PyMC

Bayesian Modeling and Probabilistic Programming in Python
numpyro

2 2,039 8.7 Python blackjax VS numpyro

Probabilistic programming with NumPy powered by JAX for autograd and JIT compilation to GPU/TPU/CPU.
Gumbi

1 48 5.2 Python blackjax VS Gumbi

Gaussian Process Model Building Interface
pgmpy

2 2,617 8.0 Python blackjax VS pgmpy

Python Library for learning (Structure and Parameter), inference (Probabilistic and Causal), and simulations in Bayesian Networks.
orbit

1 1,804 7.8 Python blackjax VS orbit

A Python package for Bayesian forecasting with object-oriented design and probabilistic models under the hood. (by uber)
WorkOS

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The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a better blackjax alternative or higher similarity.

Suggest an alternative to blackjax

blackjax reviews and mentions

Posts with mentions or reviews of blackjax. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-03-30.

AutoBNN: Probabilistic Time Series Forecasting
2 projects | news.ycombinator.com | 30 Mar 2024

What are the other four frameworks?
> For one, who wants to do stuff in tensorflow anymore let alone tensorflow-probability.
AutoBNN is a JAX library and has nothing to do technically with TF Probability. It was developed by the TF Probability team.
> DL community prefers pytorch and stats community prefers Stan.
It looks like the JAX ecosystem for stats is growing: NumPyro is based on JAX, PyMC has a JAX backend, https://github.com/blackjax-devs/blackjax has effective samplers, there is https://github.com/jax-ml/bayeux, and now AutoBNN.
> This one seems theoretically more interesting than some others but practically less useful.
Are there other factors why you think AutoBNN is not practically useful, apart from being based on the wrong foundation (which was a mistaken belief of yours)?