Alternatives and similar repositories for pyunlocbox

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

• svaiter / pyprox
  Proximal algorithms made easy in Python
  ☆59Updated 8 years ago
• locuslab / newton_admm
  A Newton ADMM based solver for Cone programming.
  ☆39Updated 8 years ago
• cvxgrp / proximal
  Sample implementations of proximal operators
  ☆194Updated 12 years ago
• dillonalaird / pysvihmm
  Implementation of stochastic variational inference for Bayesian hidden Markov models.
  ☆69Updated 7 years ago
• SheffieldML / vargplvm
  Bayesian GPLVM in MATLAB and R
  ☆75Updated 8 years ago
• thangbui / geepee
  A collection of Gaussian process models
  ☆30Updated 7 years ago
• arthurmensch / modl
  Randomized online matrix factorization
  ☆140Updated 5 years ago
• mp4096 / adawhatever
  MATLAB implementation of AdaGrad, Adam, Adamax, Adadelta etc.
  ☆33Updated 4 years ago
• jameshensman / VFF
  Variational Fourier Features
  ☆86Updated 4 years ago
• marionmari / pyGPs
  pyGPs is a library containing an object-oriented python implementation for Gaussian Process (GP) regression and classification.
  ☆216Updated 6 years ago
• akshaykgupta / SG_MCMC
  Implementation of Stochastic Gradient MCMC algorithms
  ☆41Updated 8 years ago
• Sohl-Dickstein / LAHMC
  Look Ahead Hamiltonian Monte Carlo
  ☆30Updated 10 years ago
• the-moliver / kfs
  Keras for Science
  ☆72Updated 7 years ago
• jmetzen / gp_extras
  Additional kernels that can be used with scikit-learn's Gaussian Process module
  ☆82Updated last year
• brain-research / l2hmc
  TensorFlow implementation for training MCMC samplers from the paper: Generalizing Hamiltonian Monte Carlo with Neural Network
  ☆183Updated 6 years ago
• cvxr / TFOCS
  A MATLAB toolbox for building first-order solvers for convex models.
  ☆142Updated 3 years ago
• tqchen / ML-SGHMC
  Experiment code for Stochastic Gradient Hamiltonian Monte Carlo
  ☆106Updated 7 years ago
• gpapamak / epsilon_free_inference
  Code for paper "Fast ε-free Inference of Simulation Models with Bayesian Conditional Density Estimation"
  ☆31Updated 5 years ago
• powerscorinne / GLRM
  ☆98Updated 7 years ago
• JeanKossaifi / FISTA
  Python implementation of the Fast Iterative Shrinkage/Thresholding Algorithm.
  ☆92Updated 6 years ago
• hoytak / pyksvd
  A highly optimized, parallel implementation of the Batch-OMP version of the KSVD learning algorithm.
  ☆80Updated 5 years ago
• ssydasheng / Neural-Kernel-Network
  Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326
  ☆71Updated 7 years ago
• duvenaud / deep-limits
  Repo for a paper about constructing priors on very deep models.
  ☆73Updated 9 years ago
• andymiller / ReducedVarianceReparamGradients
  Reducing Reparameterization Gradient Variance code.
  ☆33Updated 8 years ago
• imurray / chol-rev
  Backpropagate derivatives through the Cholesky decomposition
  ☆58Updated 5 years ago
• 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
• arahuja / hamiltonian-monte-carlo
  Implementation of Hamiltonian Monte Carlo using Google's TensorFlow
  ☆47Updated 9 years ago
• slinderman / pypolyagamma
  Fast C code for sampling Polya-gamma random variates. Builds on Jesse Windle's BayesLogit library.
  ☆82Updated 5 years ago
• t-vi / candlegp
  Gaussian Processes in Pytorch
  ☆75Updated 5 years ago
• karlnapf / kernel_hmc
  Code for NIPS 2015 "Gradient-Free Hamiltonian Monte Carlo via Effecient Kernel Exponential Families"
  ☆25Updated 7 years ago