Alternatives and similar repositories for aboleth

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

• RuiShu / nn-bayesian-optimization
  We use a modified neural network instead of Gaussian process for Bayesian optimization.
  ☆108Updated 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
• alshedivat / keras-gp
  Keras + Gaussian Processes: Learning scalable deep and recurrent kernels.
  ☆249Updated 10 months ago
• yaringal / DropoutUncertaintyDemos
  What My Deep Model Doesn't Know...
  ☆117Updated 9 years ago
• jameshensman / VFF
  Variational Fourier Features
  ☆86Updated 4 years ago
• stepelu / ptstat
  Probabilistic Programming and Statistical Inference in PyTorch
  ☆110Updated 7 years ago
• powerscorinne / GLRM
  ☆98Updated 7 years ago
• arogozhnikov / infiniteboost
  InfiniteBoost: building infinite ensembles with gradient descent
  ☆184Updated 6 years ago
• automl / HPOlib
  HPOlib is a hyperparameter optimization library. It provides a common interface to three state of the art hyperparameter optimization pac…
  ☆166Updated 6 years ago
• HIPS / hypergrad
  Exploring differentiation with respect to hyperparameters
  ☆295Updated 9 years ago
• edwardlib / observations
  Tools for loading standard data sets in machine learning
  ☆203Updated 2 years ago
• yaringal / DropoutUncertaintyCaffeModels
  Dropout As A Bayesian Approximation: Code
  ☆202Updated 9 years ago
• yaringal / HeteroscedasticDropoutUncertainty
  Demos demonstrating the difference between homoscedastic and heteroscedastic regression with dropout uncertainty.
  ☆140Updated 9 years ago
• casperkaae / parmesan
  Variational and semi-supervised neural network toppings for Lasagne
  ☆208Updated 8 years ago
• edwardlib / papers
  Edward content including papers, posters, and talks
  ☆91Updated 4 years ago
• bstriner / bayesian_dense
  Bayesian Weight Uncertainty Dense Layer for Keras
  ☆48Updated 8 years ago
• t-vi / candlegp
  Gaussian Processes in Pytorch
  ☆75Updated 5 years ago
• markvdw / convgp
  Convolutional Gaussian processes based on GPflow.
  ☆95Updated 7 years ago
• RobRomijnders / weight_uncertainty
  Implementing Bayes by Backprop
  ☆184Updated 6 years ago
• YingzhenLi / Dropout_BBalpha
  Implementations of the ICML 2017 paper (with Yarin Gal)
  ☆38Updated 7 years ago
• mirceamironenco / BayesianRecurrentNN
  Implementation of Bayesian Recurrent Neural Networks by Fortunato et. al
  ☆218Updated 6 years ago
• mwhoffman / pybo
  Python package for modular Bayesian optimization
  ☆135Updated 4 years ago
• janvdvegt / KernelMixtureNetwork
  Kernel Mixture Network implementation with some minor tweaks
  ☆45Updated 7 years ago
• duvenaud / deep-limits
  Repo for a paper about constructing priors on very deep models.
  ☆73Updated 8 years ago
• vene / pyowl
  Ordered Weighted L1 regularization for classification and regression in Python
  ☆52Updated 6 years ago
• larsmaaloee / auxiliary-deep-generative-models
  Deep generative models for semi-supervised learning.
  ☆108Updated 8 years ago
• tabacof / bayesian-nn-uncertainty
  Classification uncertainty using Bayesian neural networks
  ☆33Updated 8 years ago
• martius-lab / l4-optimizer
  Code for paper "L4: Practical loss-based stepsize adaptation for deep learning"
  ☆124Updated 6 years ago
• yaringal / BayesianRNN
  Code for the paper "A Theoretically Grounded Application of Dropout in Recurrent Neural Networks"
  ☆378Updated 8 years ago
• jn2clark / nn-iterated-projections
  Neural network training using iterated projections.
  ☆89Updated 8 years ago