Alternatives and similar repositories for in-depth-VI-tutorial

Users that are interested in in-depth-VI-tutorial are comparing it to the libraries listed below

• didriknielsen / ds3_abi_exercises
  Exercises for the Tutorial on Approximate Bayesian Inference at the Data Science Summer School 2018
  ☆22Updated 6 years ago
• BigBayes / SGRLD
  Stochastic Gradient Riemannian Langevin Dynamics
  ☆33Updated 9 years ago
• zixu1986 / Doubly_Stochastic_Gradients
  Code for doubly stochastic gradients
  ☆25Updated 10 years ago
• duvenaud / warped-mixtures
  Code for density estimation with nonparametric cluster shapes.
  ☆39Updated 8 years ago
• wittawatj / kernel-gof
  NeurIPS 2017 best paper. An interpretable linear-time kernel goodness-of-fit test.
  ☆67Updated 5 years ago
• rgiordan / CovariancesRobustnessVBPaper
  ☆11Updated last year
• andymiller / ReducedVarianceReparamGradients
  Reducing Reparameterization Gradient Variance code.
  ☆33Updated 7 years ago
• cchangyou / Santa
  Code for the Santa algorithm for deep learning
  ☆17Updated 7 years ago
• mrkulk / SequentialInference
  Dirichlet Process Mixture using PVI, SMC, Variational
  ☆15Updated 10 years ago
• arayabrain / GenerativeControl
  Code for a generative controller for the AI Gym cartpole task
  ☆15Updated 8 years ago
• franrruiz / vcd_divergence
  Code to minimize the Variational Contrastive Divergence (VCD)
  ☆29Updated 5 years ago
• wittawatj / kernel-mod
  NeurIPS 2018. Linear-time model comparison tests.
  ☆18Updated 5 years ago
• alshedivat / DeterminantalPointProcesses.jl
  Determinantal Point Processes in Julia
  ☆12Updated 5 years ago
• BigBayes / SMS
  Sampling via Moment Sharing
  ☆11Updated 9 years ago
• mauriziofilippone / deep_gp_random_features
  ☆40Updated 6 years ago
• uber-research / vargp
  Variational Auto-Regressive Gaussian Processes for Continual Learning
  ☆21Updated 3 years ago
• hichamjanati / mtw
  Wasserstein regularization for sparse multi-task regression
  ☆15Updated 4 years ago
• rfeinman / learning-to-learn
  Code for "Learning Inductive Biases with Simple Neural Networks" (Feinman & Lake, 2018).
  ☆22Updated 6 years ago
• wittawatj / interpretable-test
  NeurIPS 2016. Linear-time interpretable nonparametric two-sample test.
  ☆63Updated 7 years ago
• duvenaud / deep-limits
  Repo for a paper about constructing priors on very deep models.
  ☆73Updated 8 years ago
• karlnapf / ds3_kernel_testing
  Material for the practical of the DS3 course on "Representing and comparing probabilities with kernels"
  ☆26Updated 6 years ago
• vveitch / causal-embeddings
  Code for "Using Embeddings to Correct for Unobserved Confounding"
  ☆10Updated 5 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
• thjashin / gp-infer-net
  Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019
  ☆41Updated 2 years ago
• blei-lab / ars-reparameterization
  Source code for Naesseth et. al. "Reparameterization Gradients through Acceptance-Rejection Sampling Algorithms" (2017)
  ☆39Updated 8 years ago
• dillonalaird / pysvihmm
  Implementation of stochastic variational inference for Bayesian hidden Markov models.
  ☆66Updated 7 years ago
• daeilkim / bbvi
  Black Box Variational Inference
  ☆14Updated 9 years ago
• franrruiz / p-emb
  Exponential family embeddings (Poisson or Bernoulli) for discrete data
  ☆32Updated 5 years ago
• brekelma / echo
  Echo Noise Channel for Exact Mutual Information Calculation
  ☆17Updated 4 years ago
• enalisnick / paper_summaries
  Summaries and minimal implementations of ML / statistics research articles.
  ☆39Updated 4 years ago