discrete pairwise undirected graphical models
Project description
Copyright (c) 2020 Nico Piatkowski
pxpy
The python library for discrete pairwise undirected graphical models.
Changelog
1.0a22: Improved: Discretization engine, support for external inference engine. Added: default to 32bit computation (disable via env PX_USE64BIT)
1.0a21: Improved: Support for external inference engine
1.0a20: Added: Support for external inference engine (access via env PX_EXTINF)
1.0a19: Improved: Manual model creation
1.0a18: Added: Debug mode (linux only, enable via env PX_DEBUGMODE)
1.0a17: Improved: API, tests, regularization. Added: AIC and BIC computation
1.0a16: Improved: Memory management, access to optimizer state in optimization hooks. Added: Support for training resumption
1.0a15: Improved: API
1.0a14: Improved: Memory management
1.0a13: Improved: Memory management (fixed leak in conditional sampling/marginals)
1.0a12: Improved: Access to vertex and pairwise marginals
1.0a11: Added: Access to single variable marginals
1.0a10: Improved: Library build process
1.0a9: Added: Conditional sampling
1.0a8: Imroved: Maximum-a-posteriori (MAP) estimation. Added: Custom graph construction
1.0a7: Added: Conditional marginal inference, support for Ising/minimal statistics
1.0a6: Added: Manual model creation, support for training data with missing values (represented by pxpy.MISSING_VALUE)
1.0a5: Improved: Model management
1.0a4: Added: Model access in regularization and proximal hooks
1.0a3: Improved: GLIBC requirement, removed libgomp dependency
1.0a2: Added: Python 3.5 compatibility
1.0a1: Initial release
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