Alternatives and similar repositories for aboleth:

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

• alshedivat / keras-gp
  Keras + Gaussian Processes: Learning scalable deep and recurrent kernels.
  ☆249Updated 9 months ago
• stepelu / ptstat
  Probabilistic Programming and Statistical Inference in PyTorch
  ☆110Updated 7 years ago
• jameshensman / VFF
  Variational Fourier Features
  ☆84Updated 3 years ago
• arogozhnikov / infiniteboost
  InfiniteBoost: building infinite ensembles with gradient descent
  ☆184Updated 6 years ago
• RuiShu / nn-bayesian-optimization
  We use a modified neural network instead of Gaussian process for Bayesian optimization.
  ☆108Updated 7 years ago
• RobRomijnders / weight_uncertainty
  Implementing Bayes by Backprop
  ☆183Updated 6 years ago
• edwardlib / papers
  Edward content including papers, posters, and talks
  ☆91Updated 4 years ago
• martius-lab / l4-optimizer
  Code for paper "L4: Practical loss-based stepsize adaptation for deep learning"
  ☆125Updated 6 years ago
• yaringal / DropoutUncertaintyCaffeModels
  Dropout As A Bayesian Approximation: Code
  ☆201Updated 9 years ago
• edwardlib / observations
  Tools for loading standard data sets in machine learning
  ☆203Updated 2 years ago
• bstriner / bayesian_dense
  Bayesian Weight Uncertainty Dense Layer for Keras
  ☆48Updated 8 years ago
• HIPS / Probabilistic-Backpropagation
  Implementation in C and Theano of the method Probabilistic Backpropagation for scalable Bayesian inference in deep neural networks.
  ☆192Updated 6 years ago
• AI-DI / Brancher
  A user-centered Python package for differentiable probabilistic inference
  ☆202Updated 4 years ago
• t-vi / candlegp
  Gaussian Processes in Pytorch
  ☆75Updated 5 years ago
• HIPS / hypergrad
  Exploring differentiation with respect to hyperparameters
  ☆295Updated 9 years ago
• pierreablin / autoptim
  Automatic differentiation + optimization
  ☆103Updated 6 years ago
• markvdw / convgp
  Convolutional Gaussian processes based on GPflow.
  ☆96Updated 7 years ago
• janvdvegt / KernelMixtureNetwork
  Kernel Mixture Network implementation with some minor tweaks
  ☆45Updated 7 years ago
• automl / labwatch
  An extension to Sacred for automated hyperparameter optimization.
  ☆59Updated 7 years ago
• casperkaae / parmesan
  Variational and semi-supervised neural network toppings for Lasagne
  ☆208Updated 8 years ago
• mirceamironenco / BayesianRecurrentNN
  Implementation of Bayesian Recurrent Neural Networks by Fortunato et. al
  ☆218Updated 6 years ago
• YingzhenLi / Dropout_BBalpha
  Implementations of the ICML 2017 paper (with Yarin Gal)
  ☆38Updated 7 years ago
• pyprob / pyprob
  A probabilistic programming system for simulators and high-performance computing (HPC), based on PyTorch
  ☆391Updated 11 months ago
• ctallec / pyvarinf
  Python package facilitating the use of Bayesian Deep Learning methods with Variational Inference for PyTorch
  ☆359Updated 5 years ago
• yaringal / HeteroscedasticDropoutUncertainty
  Demos demonstrating the difference between homoscedastic and heteroscedastic regression with dropout uncertainty.
  ☆141Updated 9 years ago
• mwhoffman / pybo
  Python package for modular Bayesian optimization
  ☆135Updated 4 years ago
• PGM-Lab / InferPy
  InferPy: Deep Probabilistic Modeling with Tensorflow Made Easy
  ☆148Updated 9 months ago
• duvenaud / deep-limits
  Repo for a paper about constructing priors on very deep models.
  ☆73Updated 8 years ago
• LucaAmbrogioni / Functional-GP-analysis-in-Python
  A python toolbox for GP analysis written in a functional programming style
  ☆22Updated 7 years ago
• jluttine / variational-bayes-book
  Open access book on variational Bayesian methods written collaboratively
  ☆28Updated 10 years ago