Alternatives and similar repositories for Cumulative-Distribution-Transform

Users that are interested in Cumulative-Distribution-Transform are comparing it to the libraries listed below

• duvenaud / harlemcmc-shake
  Code to produce demos of Metroplis-Hastings and Hamiltonian Monte Carlo samplers.
  ☆36Updated 11 years ago
• karlnapf / kernel_hmc
  Code for NIPS 2015 "Gradient-Free Hamiltonian Monte Carlo via Effecient Kernel Exponential Families"
  ☆25Updated 7 years ago
• skolouri / Radon-Cumulative-Distribution-Transform
  Radon Cumulative Distribution Transform
  ☆25Updated 4 years ago
• mijungi / lllvm
  ☆16Updated 9 years ago
• andymiller / ReducedVarianceReparamGradients
  Reducing Reparameterization Gradient Variance code.
  ☆33Updated 8 years ago
• svaiter / pyprox
  Proximal algorithms made easy in Python
  ☆59Updated 8 years ago
• brain-research / l2hmc
  TensorFlow implementation for training MCMC samplers from the paper: Generalizing Hamiltonian Monte Carlo with Neural Network
  ☆183Updated 7 years ago
• Sohl-Dickstein / LAHMC
  Look Ahead Hamiltonian Monte Carlo
  ☆30Updated 10 years ago
• SheffieldML / vargplvm
  Bayesian GPLVM in MATLAB and R
  ☆75Updated 8 years ago
• philipphennig / probabilistic-numerics.org
  This repository houses the code for the community website http://www.probabilistic-numerics.org
  ☆36Updated 5 years ago
• gowerrobert / StochOpt.jl
  A suite of stochastic optimization methods for solving the empirical risk minimization problem.
  ☆16Updated 5 years ago
• karlnapf / kameleon-mcmc
  Code for Kernel Adaptive Metropolis-Hastings
  ☆33Updated 10 years ago
• jgorham / SteinDiscrepancy.jl
  Practical tools for quantifying how well a sample approximates a target distribution
  ☆27Updated 5 years ago
• adamhaber / JaxEnt
  Jax-based MaxEnt
  ☆17Updated 5 years ago
• davmre / gprf
  Gaussian Process Random Fields
  ☆21Updated 9 years ago
• yorkerlin / VB-MixEF
  Code for ICML 2019 paper on "Fast and Simple Natural-Gradient Variational Inference with Mixture of Exponential-family Approximations"
  ☆19Updated 4 years ago
• ebonilla / AutoGP
  Code for AutoGP
  ☆27Updated 6 years ago
• mauriziofilippone / deep_gp_random_features
  ☆40Updated 6 years ago
• daeilkim / bbvi
  Black Box Variational Inference
  ☆14Updated 10 years ago
• imurray / chol-rev
  Backpropagate derivatives through the Cholesky decomposition
  ☆58Updated 5 years ago
• tqchen / ML-SGHMC
  Experiment code for Stochastic Gradient Hamiltonian Monte Carlo
  ☆106Updated 7 years ago
• gianlucadetommaso / Stein-variational-samplers
  Python and MATLAB code for Stein Variational sampling methods
  ☆25Updated 6 years ago
• SheffieldML / deepGPy
  Deep GPs with GPy
  ☆31Updated 9 years ago
• markvdw / convgp
  Convolutional Gaussian processes based on GPflow.
  ☆95Updated 7 years ago
• wittawatj / interpretable-test
  NeurIPS 2016. Linear-time interpretable nonparametric two-sample test.
  ☆64Updated 7 years ago
• Sohl-Dickstein / Hamiltonian-Annealed-Importance-Sampling
  Matlab code implementing Hamiltonian Annealed Importance Sampling for importance weight, partition function, and log likelihood estimatio…
  ☆26Updated 11 years ago
• rgrosse / fang
  code for experiments in Grosse and Salakhutdinov, 2015.
  ☆12Updated 8 years ago
• ermongroup / a-nice-mc
  Code for "A-NICE-MC: Adversarial Training for MCMC"
  ☆126Updated 7 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
• rmcgibbo / pyhmc
  Hamiltonain Monte Carlo in Python
  ☆40Updated 5 years ago