Alternatives and similar repositories for fisher-information

Users that are interested in fisher-information are comparing it to the libraries listed below

• TaddyLab / bayesian-forest
  ☆31Updated 9 years ago
• lendle / SuPyLearner
  An implementation of the SuperLearner algorithm in Python based on scikit-learn.
  ☆25Updated 11 years ago
• balajiln / pgbart
  Particle Gibbs for Bayesian Additive Regression Trees
  ☆33Updated 10 years ago
• fonnesbeck / PyMC3_EUSS
  Course in Probabilistic Programming in Python for the 2018 EU Summer School
  ☆23Updated 7 years ago
• ebonilla / AutoGP
  Code for AutoGP
  ☆27Updated 6 years ago
• aschein / bptd
  Bayesian Poisson Tucker decomposition
  ☆17Updated 8 years ago
• ptoulis / implicit-sgd
  Using stochastic gradient descent (SGD) with explicit and implicit updates to fit large-scale statistical models.
  ☆16Updated 11 years ago
• glmgen / glmgen
  Generalized lasso implementations
  ☆46Updated last year
• pymc-learn / pymc-learn-book
  Book: Practical Probabilistic Machine Learning in Python
  ☆10Updated 4 years ago
• jameshensman / VFF
  Variational Fourier Features
  ☆86Updated 4 years ago
• itsrainingdata / sparsebn
  Software for learning sparse Bayesian networks
  ☆42Updated 5 years ago
• BigBayes / SGRLD
  Stochastic Gradient Riemannian Langevin Dynamics
  ☆34Updated 10 years ago
• sods / ods
  Open Data Science
  ☆33Updated last year
• hcllaw / bdr
  Perform bayesian distribution regression
  ☆13Updated 7 years ago
• lopezpaz / causation_learning_theory
  Code for "Towards a learning theory of cause-effect inference" (ICML 2015).
  ☆30Updated 5 years ago
• ahug / amld-pytorch-workshop
  Introduction to PyTorch Workshop at the AMLD 2019
  ☆31Updated 6 years ago
• tansey / hrt
  The holdout randomization test: feature selection using black box predictive models
  ☆22Updated 4 years ago
• NICTA / revrand
  A library of scalable Bayesian generalised linear models with fancy features
  ☆60Updated 8 years ago
• frank-hutter / fanova
  Functional ANOVA
  ☆28Updated 11 years ago
• dmarcous / CRAN_deepboost
  Deepboost R-package for submission
  ☆19Updated 8 years ago
• ivaleraM / GLFM
  General Latent Feature Modeling for Heterogeneous data
  ☆50Updated last year
• adtech-labs / bayes_logistic
  Bayesian Logistic Regression using Laplace approximations to the posterior.
  ☆48Updated 8 years ago
• cavaunpeu / random-effects-neural-networks
  Random effects neural networks with Edward and Keras
  ☆14Updated 8 years ago
• tbjohns / BlitzL1
  Fast, principled L1-regularized loss minimization
  ☆24Updated last year
• wittawatj / interpretable-test
  NeurIPS 2016. Linear-time interpretable nonparametric two-sample test.
  ☆64Updated 7 years ago
• davharris / mcmc-tutorial
  Tutorial introducing Monte Carlo integration and Markov Chain Monte Carlo
  ☆52Updated 12 years ago
• PMBio / pygp
  A Gaussian process toolbox in python
  ☆42Updated 13 years ago
• junpenglao / Bayesian-Cognitive-Modeling-in-Pymc3
  PyMC3 codes of Lee and Wagenmakers' Bayesian Cognitive Modeling - A Pratical Course
  ☆96Updated 8 years ago
• edwardlib / papers
  Edward content including papers, posters, and talks
  ☆92Updated 5 years ago
• dswah / sgcrfpy
  SGCRFpy: Sparse Gaussian Conditional Random Fields in Python
  ☆30Updated 9 years ago