Alternatives and similar repositories for awesome-bayesian-deep-learning

Users that are interested in awesome-bayesian-deep-learning are comparing it to the libraries listed below

• joanbruna / MathsDL-spring18
  Topics course Mathematics of Deep Learning, NYU, Spring 18
  ☆548Updated 2 years ago
• yaringal / BayesianRNN
  Code for the paper "A Theoretically Grounded Application of Dropout in Recurrent Neural Networks"
  ☆380Updated 8 years ago
• ctallec / pyvarinf
  Python package facilitating the use of Bayesian Deep Learning methods with Variational Inference for PyTorch
  ☆361Updated 6 years ago
• wiseodd / probabilistic-models
  Collection of probabilistic models and inference algorithms
  ☆240Updated 5 years ago
• probtorch / probtorch
  Probabilistic Torch is library for deep generative models that extends PyTorch
  ☆894Updated last year
• Kyubyong / pytorch_exercises
  ☆317Updated 8 years ago
• LMescheder / AdversarialVariationalBayes
  This repository contains the code to reproduce the core results from the paper "Adversarial Variational Bayes: Unifying Variational Autoe…
  ☆208Updated 7 years ago
• hindupuravinash / nips2016
  A list of resources for all invited talks, tutorials, workshops and presentations at NIPS 2016
  ☆223Updated 8 years ago
• yaringal / DropoutUncertaintyCaffeModels
  Dropout As A Bayesian Approximation: Code
  ☆204Updated 10 years ago
• mila-iqia / welcome_tutorials
  Various tutorials given for welcoming new students at MILA.
  ☆986Updated 7 years ago
• mirceamironenco / BayesianRecurrentNN
  Implementation of Bayesian Recurrent Neural Networks by Fortunato et. al
  ☆220Updated 7 years ago
• vasiloglou / mltrain-nips-2017
  This repository contains all the material for the MLTrain NIPS workshop
  ☆244Updated 8 years ago
• rinuboney / ladder
  Ladder network is a deep learning algorithm that combines supervised and unsupervised learning.
  ☆242Updated 8 years ago
• daviddao / awesome-very-deep-learning
  ♾A curated list of papers and code about very deep neural networks
  ☆454Updated 5 years ago
• hoangcuong2011 / Good-Papers
  I try my best to keep updated cutting-edge knowledge in Machine Learning/Deep Learning and Natural Language Processing. These are my not…
  ☆285Updated 6 years ago
• hardmaru / pytorch_notebooks
  tutorial notebooks
  ☆391Updated 7 years ago
• sangwoomo / ml-resources
  Personal and biased selection of ML resources
  ☆151Updated 5 years ago
• kihosuh / nips_2017
  videos, slides, and others from NIPS 2017
  ☆180Updated 7 years ago
• sjchoi86 / bayes-nn
  Lecture notes on Bayesian deep learning
  ☆488Updated 7 years ago
• vinhkhuc / PyTorch-Mini-Tutorials
  Minimal tutorials for PyTorch
  ☆329Updated 5 years ago
• karpathy / paper-notes
  Random notes on papers, likely a short-term repo.
  ☆700Updated 8 years ago
• abhshkdz / papers
  Summaries of papers on deep learning
  ☆571Updated 6 years ago
• dpkingma / nips14-ssl
  Code for reproducing results of NIPS 2014 paper "Semi-Supervised Learning with Deep Generative Models"
  ☆515Updated 10 years ago
• a913cb82 / CSML_notes
  UCL MSc Computational Statistics and Machine Learning Revision Notes
  ☆289Updated 7 years ago
• bfortuner / pytorch-cheatsheet
  Check out improved:
  ☆299Updated 8 years ago
• RobRomijnders / weight_uncertainty
  Implementing Bayes by Backprop
  ☆184Updated 6 years ago
• RuiShu / nn-bayesian-optimization
  We use a modified neural network instead of Gaussian process for Bayesian optimization.
  ☆108Updated 8 years ago
• Kaixhin / Autoencoders
  Torch implementations of various types of autoencoders
  ☆476Updated 8 years ago
• oduerr / dl_tutorial
  Tutorials for deep learning
  ☆254Updated 7 years ago
• y0ast / Variational-Autoencoder
  Implementation of a Variational Auto-Encoder in Theano
  ☆381Updated 8 years ago