PyMC: a modern, and comprehensive probabilistic programming framework in Python
Boston University · Google (United States) · +12 more institutions
Abstract
PyMC is a probabilistic programming library for Python that provides tools for constructing and fitting Bayesian models. It offers an intuitive, readable syntax that is close to the natural syntax statisticians use to describe models. PyMC leverages the symbolic computation library PyTensor, allowing it to be compiled into a variety of computational backends, such as C, JAX, and Numba, which in turn offer access to different computational architectures including CPU, GPU, and TPU. Being a general modeling framework, PyMC supports a variety of models including generalized hierarchical linear regression and classification, time series, ordinary differential equations (ODEs), and non-parametric models such as…
Citation impact
- FWCI
- 92.97
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- 100%
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Authors
14Topics & keywords
- Computer science
- Python (programming language)
- Probabilistic logic
- Programming language
- Syntax
- Theoretical computer science
- Statistical model
- Variety (cybernetics)
- Life in Land