Alternatives and similar repositories for 2017-JMLR-MCMCForTallData

Users that are interested in 2017-JMLR-MCMCForTallData are comparing it to the libraries listed below

• hughsalimbeni / bayesian_benchmarks
  A community repository for benchmarking Bayesian methods
  ☆112Updated 4 years ago
• trevorcampbell / bayesian-coresets
  Automated Scalable Bayesian Inference
  ☆131Updated 4 years ago
• wjmaddox / drbayes
  Code Repo for "Subspace Inference for Bayesian Deep Learning"
  ☆83Updated last year
• guilgautier / DPPy
  Python toolbox for sampling Determinantal Point Processes
  ☆237Updated last year
• hichamjanati / srf
  Random Fourier Features
  ☆50Updated 8 years ago
• UCL-SML / Doubly-Stochastic-DGP
  Deep Gaussian Processes with Doubly Stochastic Variational Inference
  ☆151Updated 6 years ago
• wittawatj / kernel-cgof
  UAI 2020. Kernel goodness-of-fit tests for conditional density models.
  ☆10Updated 5 years ago
• brain-research / nngp
  Deep neural network kernel for Gaussian process
  ☆212Updated 5 years ago
• otokonoko8 / deep-Bayesian-nonparametrics-papers
  The collection of papers about combining deep learning and Bayesian nonparametrics
  ☆122Updated 6 years ago
• ChunyuanLI / SVGD
  Tensorflow implementation of Stein Variational Gradient Descent (SVGD)
  ☆26Updated 8 years ago
• nitarshan / bayes-by-backprop
  PyTorch implementation of "Weight Uncertainty in Neural Networks"
  ☆176Updated 3 years ago
• otokonoko8 / implicit-variational-inference
  The collection of recent papers about variational inference
  ☆84Updated 6 years ago
• DartML / Stein-Variational-Gradient-Descent
  code for the paper "Stein Variational Gradient Descent (SVGD): A General Purpose Bayesian Inference Algorithm"
  ☆101Updated 6 years ago
• ialong / GPt
  Gaussian Processes for Sequential Data
  ☆19Updated 5 years ago
• oxcsml / ML_bazaar
  OxCSML research group reading groups and meetings at the Department of Statistics, University of Oxford.
  ☆96Updated 4 years ago
• jmikko / fair_ERM
  Fair Empirical Risk Minimization (FERM)
  ☆37Updated 5 years ago
• csquires / causal-rep-learning-reading-group
  ☆22Updated 2 years ago
• team-approx-bayes / dnn2gp
  Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)
  ☆48Updated 6 years ago
• izmailovpavel / understandingbdl
  ☆252Updated 3 years ago
• egstatsml / arxivsearch
  Pulls papers from arXiv on a weekly basis
  ☆30Updated 2 years ago
• blei-lab / variational-smc
  Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)
  ☆66Updated 6 years ago
• karlnapf / kernel_exp_family
  Various estimators of the infinite dimensional exponential family model
  ☆16Updated 8 years ago
• keyonvafa / logistic-reg-bbvi-blog
  Black Box Variational Inference for Bayesian logistic regression
  ☆18Updated 8 years ago
• ssydasheng / FBNN
  Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)
  ☆86Updated 5 years ago
• google-deepmind / mc_gradients
  ☆172Updated last year
• microsoft / deterministic-variational-inference
  Sample code for running deterministic variational inference to train Bayesian neural networks
  ☆102Updated 7 years ago
• namkoong-lab / robustopt
  ☆43Updated 7 years ago
• TeaPearce / Bayesian_NN_Ensembles
  AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'
  ☆90Updated 5 years ago
• Human-Centric-Machine-Learning / hdhp.py
  Code for "Hierarchical Dirichlet-Hawkes process: generative model and inference algorithm", WWW 2017
  ☆36Updated 7 years ago
• mingzhang-yin / SIVI
  A variational inference method with accurate uncertainty estimation. It uses a new semi-implicit variational family built on neural netwo…
  ☆54Updated last year