Alternatives and similar repositories for paper_summaries:

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

• cmaddis / astar-sampling
  A generic Monte Carlo method based on the Gumbel-Max trick.
  ☆32Updated 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
• Bonnevie / rebar
  A Python implementation of the gradient REBAR estimator.
  ☆46Updated 6 years ago
• andymiller / ReducedVarianceReparamGradients
  Reducing Reparameterization Gradient Variance code.
  ☆33Updated 7 years ago
• rhaps0dy / convnets-as-gps
  Code for "Deep Convolutional Networks as shallow Gaussian Processes"
  ☆39Updated 5 years ago
• duvenaud / deep-limits
  Repo for a paper about constructing priors on very deep models.
  ☆72Updated 8 years ago
• t-vi / candlegp
  Gaussian Processes in Pytorch
  ☆75Updated 4 years ago
• adjidieng / REM
  Reweighted Expectation Maximization
  ☆29Updated 5 years ago
• akshaykgupta / SG_MCMC
  Implementation of Stochastic Gradient MCMC algorithms
  ☆40Updated 8 years ago
• wittawatj / interpretable-test
  NeurIPS 2016. Linear-time interpretable nonparametric two-sample test.
  ☆63Updated 6 years ago
• wittawatj / kernel-gof
  NeurIPS 2017 best paper. An interpretable linear-time kernel goodness-of-fit test.
  ☆67Updated 5 years ago
• brekelma / echo
  Echo Noise Channel for Exact Mutual Information Calculation
  ☆17Updated 4 years ago
• y0ast / VIMCO
  Implementation of "Variational Inference for Monte Carlo Objectives"
  ☆21Updated 4 years ago
• CW-Huang / torchkit
  ☆37Updated 5 years ago
• wittawatj / kernel-mod
  NeurIPS 2018. Linear-time model comparison tests.
  ☆18Updated 4 years ago
• casmls / casmls.github.io
  Columbia Advanced Machine Learning Seminar
  ☆24Updated 6 years ago
• rachtsingh / lgamma
  Implementations of polygamma, lgamma, and beta functions for PyTorch
  ☆24Updated 7 years ago
• zihangdai / cegan_iclr2017
  Code release for the paper "Calibrating Energy-based Generative Adversarial Networks"
  ☆23Updated 7 years ago
• AMLab-Amsterdam / MNF_VBNN
  Multiplicative Normalizing Flow (MNF) posteriors for variational Bayesian neural networks
  ☆65Updated 4 years ago
• jiamings / ais
  Annealed Importance Sampling (AIS) for generative models.
  ☆16Updated 6 years ago
• csc2541-f17 / csc2541-f17.github.io
  ☆12Updated 7 years ago
• approximateinference / approximateinference.github.io
  NeurIPS workshop on Advances in Approximate Bayesian Inference
  ☆48Updated this week
• emtiyaz / vmp-for-svae
  Variational Message Passing for Structured VAE (Code for ICLR 2018 paper)
  ☆44Updated 6 years ago
• mauriziofilippone / deep_gp_random_features
  ☆40Updated 5 years ago
• IraKorshunova / bruno
  a deep recurrent model for exchangeable data
  ☆34Updated 4 years ago
• joelouismarino / iterative_inference
  Implementation of iterative inference in deep latent variable models
  ☆43Updated 5 years ago
• Sohl-Dickstein / Minimum-Probability-Flow-Learning
  Matlab code implementing Minimum Probability Flow Learning.
  ☆68Updated 10 years ago
• PrincetonLIPS / randomized_telescopes
  Code for "Efficient optimization of loops and limits with randomized telescoping sums"
  ☆27Updated 5 years ago
• thjashin / gp-infer-net
  Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019
  ☆41Updated 2 years ago