Alternatives and similar repositories for yaglm

Users that are interested in yaglm are comparing it to the libraries listed below

• scikit-learn-contrib / skglm
  Fast and modular sklearn replacement for generalized linear models
  ☆191Updated 4 months ago
• flatironinstitute / bayes-kit
  Bayesian inference and posterior analysis for Python
  ☆46Updated 2 years ago
• mathurinm / celer
  Fast solver for L1-type problems: Lasso, sparse Logisitic regression, Group Lasso, weighted Lasso, Multitask Lasso, etc.
  ☆237Updated 7 months ago
• arviz-devs / preliz
  Exploring and eliciting probability distributions
  ☆162Updated last month
• bambinos / formulae
  Formulas for mixed-effects models in Python
  ☆64Updated 3 weeks ago
• BasisResearch / millipede
  A library for bayesian variable selection
  ☆31Updated last year
• pyro-ppl / brmp
  Bayesian Regression Models in Pyro
  ☆74Updated last year
• aesara-devs / aeppl
  Tools for an Aesara-based PPL.
  ☆67Updated last year
• fabian-sp / GGLasso
  A Python package for General Graphical Lasso computation
  ☆40Updated 11 months ago
• eth-cscs / abcpy
  ABCpy package
  ☆117Updated 2 weeks ago
• pymc-devs / sunode
  Solve ODEs fast, with support for PyMC
  ☆119Updated last year
• acerbilab / pyvbmc
  PyVBMC: Variational Bayesian Monte Carlo algorithm for posterior and model inference in Python
  ☆123Updated last month
• stan-dev / posteriordb
  Database with posteriors of interest for Bayesian inference
  ☆212Updated this week
• justindomke / pangolin
  probabilistic programming focused on fun
  ☆49Updated 2 weeks ago
• arviz-devs / simuk
  Simulation based calibration and generation of synthetic data.
  ☆56Updated 2 months ago
• aesara-devs / aemcmc
  AeMCMC is a Python library that automates the construction of samplers for Aesara graphs representing statistical models.
  ☆39Updated 2 years ago
• blackjax-devs / sampling-book
  Tutorials and sampling algorithm comparisons
  ☆79Updated this week
• ecotner / statistical-rethinking
  Following along with Statistical Rethinking text on Bayesian modeling by McElreath
  ☆70Updated 5 years ago
• Yu-Group / veridical-flow
  Making it easier to build stable, trustworthy data-science pipelines based on the PCS framework.
  ☆72Updated last year
• abhiagwl / vistan
  A simple library to run variational inference on Stan models.
  ☆33Updated 2 years ago
• neurodata / treeple
  Scikit-learn compatible decision trees beyond those offered in scikit-learn
  ☆86Updated last week
• jax-ml / bayeux
  State of the art inference for your bayesian models.
  ☆231Updated 3 weeks ago
• wesselb / stheno
  Gaussian process modelling in Python
  ☆226Updated last year
• ColCarroll / minimc
  Just a little MCMC
  ☆235Updated last year
• pymc-devs / pymc-extras
  Powerful add-ons for PyMC
  ☆133Updated this week
• jhuggins / viabel
  Efficient, lightweight variational inference and approximation bounds
  ☆46Updated 3 months ago
• scikit-hep / resample
  Randomization-based inference in Python
  ☆84Updated last week
• bob-carpenter / walnuts
  Step size adaptation for the No-U-Turn Sampler
  ☆26Updated 2 months ago
• pymc-devs / nutpie
  Python wrapper for nuts-rs
  ☆188Updated this week
• AmpersandTV / pymc3-hmm
  Hidden Markov models in PyMC3
  ☆96Updated last year