Alternatives and similar repositories for paramz

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

• ziyuw / rembo
  Bayesian optimization in high-dimensions via random embedding.
  ☆114Updated 12 years ago
• b45ch1 / algopy
  AlgoPy is a Research Prototype for Algorithmic Differentation in Python
  ☆85Updated last year
• jmetzen / gp_extras
  Additional kernels that can be used with scikit-learn's Gaussian Process module
  ☆82Updated last year
• SheffieldML / deepGP
  Deep Gaussian Processes in matlab
  ☆93Updated 3 years ago
• SheffieldML / notebook
  Collection of jupyter notebooks for demonstrating software.
  ☆169Updated 2 years ago
• ffx-org / ffx
  Fast Function Extraction
  ☆85Updated last month
• duvenaud / phd-thesis
  I am in [research] stepped in so far that, should I wade no more, Returning were as tedious as go o'er. -MacBeth
  ☆185Updated 11 years ago
• cvxgrp / cvxflow
  ☆67Updated 7 years ago
• jmetzen / bayesian_optimization
  Bayesian optimization
  ☆38Updated 5 years ago
• Sohl-Dickstein / LAHMC
  Look Ahead Hamiltonian Monte Carlo
  ☆30Updated 10 years ago
• sigopt / evalset
  Benchmark suite of test functions suitable for evaluating black-box optimization strategies
  ☆52Updated 3 months ago
• PMBio / pygp
  A Gaussian process toolbox in python
  ☆42Updated 13 years ago
• andymiller / ReducedVarianceReparamGradients
  Reducing Reparameterization Gradient Variance code.
  ☆33Updated 8 years ago
• mwhoffman / pybo
  Python package for modular Bayesian optimization
  ☆136Updated 4 years ago
• UCL-SML / Doubly-Stochastic-DGP
  Deep Gaussian Processes with Doubly Stochastic Variational Inference
  ☆150Updated 6 years ago
• amzn / MXFusion
  Modular Probabilistic Programming on MXNet
  ☆104Updated 2 years ago
• karlnapf / kernel_hmc
  Code for NIPS 2015 "Gradient-Free Hamiltonian Monte Carlo via Effecient Kernel Exponential Families"
  ☆25Updated 7 years ago
• jamesrobertlloyd / gpss-research
  Kernel structure discovery research code - likely to be unstable
  ☆191Updated 10 years ago
• vlad17 / runlmc
  Structurally efficient multi-output linearly coregionalized Gaussian Processes: it's tricky, tricky, tricky, tricky, tricky.
  ☆38Updated 2 years ago
• philipphennig / probabilistic-numerics.org
  This repository houses the code for the community website http://www.probabilistic-numerics.org
  ☆36Updated 5 years ago
• alshedivat / keras-gp
  Keras + Gaussian Processes: Learning scalable deep and recurrent kernels.
  ☆249Updated last year
• marionmari / pyGPs
  pyGPs is a library containing an object-oriented python implementation for Gaussian Process (GP) regression and classification.
  ☆216Updated 6 years ago
• karlnapf / kameleon-mcmc
  Code for Kernel Adaptive Metropolis-Hastings
  ☆33Updated 10 years ago
• maziarraissi / ParametricGP
  Parametric Gaussian Process Regression for Big Data
  ☆45Updated 5 years ago
• NICTA / revrand
  A library of scalable Bayesian generalised linear models with fancy features
  ☆60Updated 7 years ago
• akshaykgupta / SG_MCMC
  Implementation of Stochastic Gradient MCMC algorithms
  ☆41Updated 8 years ago
• thangbui / geepee
  A collection of Gaussian process models
  ☆30Updated 8 years ago
• oxfordcontrol / Bayesian-Optimization
  Reference implementation of Optimistic Expected Improvement.
  ☆49Updated 5 years ago
• markvdw / convgp
  Convolutional Gaussian processes based on GPflow.
  ☆95Updated 7 years ago
• andim / noisyopt
  Python library for optimizing noisy functions.
  ☆88Updated 3 years ago