Alternatives and similar repositories for JVHW_Entropy_Estimators

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

• henripal / sgld
  ☆59Updated 6 years ago
• wjmaddox / spectralgp
  Code repo for "Function-Space Distributions over Kernels"
  ☆32Updated 4 years ago
• blei-lab / variational-smc
  Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)
  ☆65Updated 6 years ago
• dimkal89 / rvae
  ☆38Updated 5 years ago
• wangleiphy / MongeAmpereFlow
  Continuous-time gradient flow for generative modeling and variational inference
  ☆33Updated 6 years ago
• ganguli-lab / deepchaos
  Experiments for the paper "Exponential expressivity in deep neural networks through transient chaos"
  ☆72Updated 9 years ago
• karlnapf / kernel_exp_family
  Various estimators of the infinite dimensional exponential family model
  ☆15Updated 8 years ago
• didriknielsen / ds3_abi_exercises
  Exercises for the Tutorial on Approximate Bayesian Inference at the Data Science Summer School 2018
  ☆22Updated 7 years ago
• izmailovpavel / TTGP
  ☆26Updated 7 years ago
• otokonoko8 / deep-Bayesian-nonparametrics-papers
  The collection of papers about combining deep learning and Bayesian nonparametrics
  ☆121Updated 5 years ago
• ae-foster / dad
  Deep Adaptive Design: Amortizing Sequential Bayesian Experimental Design
  ☆36Updated 4 years ago
• BiuBiuBiLL / NPEET_LNC
  local non-uniformity correction for mutual information estimation
  ☆70Updated 4 years ago
• oxcsml / ML_bazaar
  OxCSML research group reading groups and meetings at the Department of Statistics, University of Oxford.
  ☆93Updated 3 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
• jaanli / hierarchical-variational-models-physics
  Hierarchical variational models for physics.
  ☆18Updated 5 years ago
• aboustati / dgplib
  Library for Deep Gaussian Processes based on GPflow
  ☆19Updated 5 years ago
• rmgarnett / cse515t
  Materials for Bayesian Methods in Machine Learning Course
  ☆90Updated 2 weeks ago
• hughsalimbeni / bayesian_benchmarks
  A community repository for benchmarking Bayesian methods
  ☆110Updated 3 years ago
• mackelab / delfi
  Density estimation likelihood-free inference. No longer actively developed see https://github.com/mackelab/sbi instead
  ☆73Updated 5 years ago
• audeg / StochasticOT
  Stochastic Optimization for Optimal Transport
  ☆22Updated 8 years ago
• MFreidank / pysgmcmc
  Bayesian Deep Learning with Stochastic Gradient MCMC Methods
  ☆39Updated 4 years ago
• karlnapf / kernel_hmc
  Code for NIPS 2015 "Gradient-Free Hamiltonian Monte Carlo via Effecient Kernel Exponential Families"
  ☆25Updated 7 years ago
• google-deepmind / mc_gradients
  ☆170Updated last year
• conormdurkan / lfi
  Neural likelihood-free methods in PyTorch.
  ☆39Updated 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
• akshaykgupta / SG_MCMC
  Implementation of Stochastic Gradient MCMC algorithms
  ☆41Updated 8 years ago
• glajoie / MAT6115_Dynamical_Systems
  Support material for MAT6115, Université de Montréal, Fall 2018
  ☆27Updated last year
• mauriziofilippone / deep_gp_random_features
  ☆40Updated 6 years ago
• gianlucadetommaso / Stein-variational-samplers
  Python and MATLAB code for Stein Variational sampling methods
  ☆25Updated 6 years ago
• franrruiz / vcd_divergence
  Code to minimize the Variational Contrastive Divergence (VCD)
  ☆29Updated 6 years ago