jluttine / variational-bayes-book

Related projects ⓘ

Alternatives and complementary repositories for variational-bayes-book

• andymiller / ReducedVarianceReparamGradients
  Reducing Reparameterization Gradient Variance code.
  ☆33Updated 7 years ago
• duvenaud / deep-limits
  Repo for a paper about constructing priors on very deep models.
  ☆70Updated 8 years ago
• rgiordan / CovariancesRobustnessVBPaper
  ☆12Updated last year
• casmls / casmls.github.io
  Columbia Advanced Machine Learning Seminar
  ☆24Updated 6 years ago
• Sohl-Dickstein / Minimum-Probability-Flow-Learning
  Matlab code implementing Minimum Probability Flow Learning.
  ☆68Updated 10 years ago
• ssydasheng / Neural-Kernel-Network
  Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326
  ☆71Updated 6 years ago
• HIPS / maxwells-daemon
  Fastidious accounting of entropy streams into and out of optimization and sampling algorithms.
  ☆31Updated 8 years ago
• jameshensman / VFF
  Variational Fourier Features
  ☆83Updated 3 years ago
• TENGBINN / Bayes-by-Backprop
  TensorFlow implementation of Bayes-by-Backprop algorithm from "Weight Uncertainty in Neural Networks" paper
  ☆51Updated 5 years ago
• enalisnick / paper_summaries
  Summaries and minimal implementations of ML / statistics research articles.
  ☆39Updated 3 years ago
• emtiyaz / vmp-for-svae
  Variational Message Passing for Structured VAE (Code for ICLR 2018 paper)
  ☆44Updated 6 years ago
• t-vi / candlegp
  Gaussian Processes in Pytorch
  ☆74Updated 4 years ago
• duvenaud / warped-mixtures
  Code for density estimation with nonparametric cluster shapes.
  ☆38Updated 8 years ago
• AMLab-Amsterdam / SEVDL_MGP
  Example implementation of the Bayesian neural network in "Structured and Efficient Variational Deep Learning with Matrix Gaussian Posteri…
  ☆31Updated 4 years ago
• akshaykgupta / SG_MCMC
  Implementation of Stochastic Gradient MCMC algorithms
  ☆40Updated 7 years ago
• brekelma / echo
  Echo Noise Channel for Exact Mutual Information Calculation
  ☆17Updated 4 years ago
• blei-lab / zero-inflated-embedding
  Code for the icml paper "zero inflated exponential family embedding"
  ☆29Updated 7 years ago
• thangbui / geepee
  A collection of Gaussian process models
  ☆30Updated 7 years ago
• RuiShu / tensorbayes
  Deep variational inference in tensorflow
  ☆56Updated 6 years ago
• karlnapf / kernel_hmc
  Code for NIPS 2015 "Gradient-Free Hamiltonian Monte Carlo via Effecient Kernel Exponential Families"
  ☆24Updated 6 years ago
• dillonalaird / pysvihmm
  Implementation of stochastic variational inference for Bayesian hidden Markov models.
  ☆65Updated 7 years ago
• BigBayes / SGRLD
  Stochastic Gradient Riemannian Langevin Dynamics
  ☆33Updated 9 years ago
• wittawatj / kernel-gof
  NeurIPS 2017 best paper. An interpretable linear-time kernel goodness-of-fit test.
  ☆67Updated 5 years ago
• tbroderick / streaming_vb
  This is code associated with the paper: Broderick, T, Boyd, N, Wibisono, A, Wilson, AC, and Jordan, MI. Streaming variational Bayes. Neur…
  ☆41Updated 10 years ago
• mrkulk / SequentialInference
  Dirichlet Process Mixture using PVI, SMC, Variational
  ☆15Updated 10 years ago
• stokasto / sgmcmc
  Stochastic Gradient MCMC algorithms implemented in theano (and autograd)
  ☆9Updated 7 years ago
• myshkov / bnn-analysis
  ☆15Updated 7 years ago
• yaoli / nade_k
  An iterative neural autoregressive distribution estimator (NADE-K)
  ☆26Updated 10 years ago
• jaanli / proximity_vi
  This code accompanies the proximity variational inference paper.
  ☆18Updated 5 years ago
• premgopalan / bnprec
  Gopalan, P., Ruiz, F. J., Ranganath, R., & Blei, D. M. (2014). Bayesian Nonparametric Poisson Factorization for Recommendation Systems. I…
  ☆15Updated 10 years ago