{ "info": { "author": "Colin Clement", "author_email": "colin.clement@gmail.com", "bugtrack_url": null, "classifiers": [ "Development Status :: 2 - Pre-Alpha", "Intended Audience :: Science/Research", "License :: OSI Approved :: MIT License", "Operating System :: OS Independent", "Programming Language :: Python", "Programming Language :: Python :: 3", "Topic :: Scientific/Engineering :: Artificial Intelligence", "Topic :: Scientific/Engineering :: Information Analysis", "Topic :: Scientific/Engineering :: Mathematics" ], "description": "Variational Bayesian Inference Toolbox\n\n--------------------------------------\n\n\nThis module is inspired by the paper 'Black Box Variational Inference'\nby Rajesh Ranganath et al. It attempts to make nearly trivial the task\nof fitting a variational distribution to a user-specified log-likelihood\nfunction without derivatives. Currently it only uses a\nmean field variational distribution, but the main class \nVariationalInferenceMF is flexible enough for simple subclassing in the\nfuture. This module also contains a number of implementations of\nstochastic gradient descent algorithms to be used for optimization.\n\n\n", "description_content_type": null, "docs_url": null, "download_url": "", "downloads": { "last_day": -1, "last_month": -1, "last_week": -1 }, "home_page": "https://github.com/colinclement/varibayes", "keywords": "variational bayes inference", "license": "MIT License", "maintainer": "", "maintainer_email": "", "name": "varibayes", "package_url": "https://pypi.org/project/varibayes/", "platform": "any", "project_url": "https://pypi.org/project/varibayes/", "project_urls": { "Homepage": "https://github.com/colinclement/varibayes" }, "release_url": "https://pypi.org/project/varibayes/0.0.1/", "requires_dist": [ "numpy (>=1.10.4)" ], "requires_python": "", "summary": "A toolbox for performing variational Bayesian inference", "version": "0.0.1" }, "last_serial": 3264485, "releases": { "0.0.1": [ { "comment_text": "", "digests": { "md5": "ff5fd4299f70992298a6f557a4c07a61", "sha256": "c584eeca7c8f2fbedc04ba2474e0c0d52978f1e9d668011ac12a9b5d9aaafcaf" }, "downloads": -1, "filename": "varibayes-0.0.1-py2.py3-none-any.whl", "has_sig": false, "md5_digest": "ff5fd4299f70992298a6f557a4c07a61", "packagetype": "bdist_wheel", "python_version": "py2.py3", "requires_python": null, "size": 8007, "upload_time": "2017-10-20T02:48:36", "url": "https://files.pythonhosted.org/packages/d1/43/b7c1431c3efddc0bea84ca0a26e5061e69c71484b9e800ec513bddc7f5d9/varibayes-0.0.1-py2.py3-none-any.whl" } ] }, "urls": [ { "comment_text": "", "digests": { "md5": "ff5fd4299f70992298a6f557a4c07a61", "sha256": "c584eeca7c8f2fbedc04ba2474e0c0d52978f1e9d668011ac12a9b5d9aaafcaf" }, "downloads": -1, "filename": "varibayes-0.0.1-py2.py3-none-any.whl", "has_sig": false, "md5_digest": "ff5fd4299f70992298a6f557a4c07a61", "packagetype": "bdist_wheel", "python_version": "py2.py3", "requires_python": null, "size": 8007, "upload_time": "2017-10-20T02:48:36", "url": "https://files.pythonhosted.org/packages/d1/43/b7c1431c3efddc0bea84ca0a26e5061e69c71484b9e800ec513bddc7f5d9/varibayes-0.0.1-py2.py3-none-any.whl" } ] }