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PyMC3

Probabilistic programming in Python

PyMC3 allows you to write down models using an intuitive syntax to describe a data generating process. Fit your model using gradient-based MCMC algorithms like NUTS, using ADVI for fast approximate inference — including minibatch-ADVI for scaling to large datasets, or using Gaussian processes to build Bayesian nonparametric models. PyMC3 includes a comprehensive set of pre-defined statistical distributions that can be used as model building blocks.

Downloads: 0 This Week

Last Update: 2026-05-20
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2

Adaptive Simulated Annealing (ASA)

simulated annealing optimization and importance-sampling

Adaptive Simulated Annealing (ASA) is a C-language code that finds the best global fit of a nonlinear cost-function over a D-dimensional space. ASA has over 100 OPTIONS to provide robust tuning over many classes of nonlinear stochastic systems.

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Downloads: 1 This Week

Last Update: 2024-04-10
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