Alternatives and similar repositories for tutorials

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

• mlss-skoltech / lectures
  repository with the lectures for MLSS Skoltech
  ☆139Updated 5 years ago
• bayesgroup / bayesgroup.github.io
  ☆82Updated 2 years ago
• SummerSchoolMachineLearning / SMILES2020
  Repository with all material for SMILES, the Summer School of Machine Learning at Skoltech, taking place from the 16th to the 21st of Aug…
  ☆55Updated 4 years ago
• HolyBayes / pytorch_ard
  Pytorch implementation of Variational Dropout Sparsifies Deep Neural Networks
  ☆83Updated 3 years ago
• aiwabdn / pygln
  Python implementation of GLN in different frameworks
  ☆97Updated 4 years ago
• duvenaud / learn-discrete
  Graduate topics course on learning discrete latent structure.
  ☆67Updated 6 years ago
• xgfs / imd
  Code for MSID, a Multi-Scale Intrinsic Distance for comparing generative models, studying neural networks, and more!
  ☆51Updated 6 years ago
• ruqizhang / csgmcmc
  Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning
  ☆92Updated 4 years ago
• RobRomijnders / weight_uncertainty
  Implementing Bayes by Backprop
  ☆184Updated 6 years ago
• joanbruna / MathsDL-spring19
  Mathematics of Deep Learning, Courant Insititute, Spring 19
  ☆277Updated 6 years ago
• emtiyaz / vadam
  Code for ICML 2018 paper on "Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam" by Khan, Nielsen, Tangkaratt, Lin, …
  ☆112Updated 6 years ago
• mblondel / fenchel-young-losses
  Probabilistic classification in PyTorch/TensorFlow/scikit-learn with Fenchel-Young losses
  ☆186Updated last year
• abdulfatir / normalizing-flows
  Understanding normalizing flows
  ☆132Updated 5 years ago
• wjmaddox / drbayes
  Code Repo for "Subspace Inference for Bayesian Deep Learning"
  ☆82Updated last year
• hardmaru / mdn_jax_tutorial
  Mixture Density Networks (Bishop, 1994) tutorial in JAX
  ☆60Updated 5 years ago
• akosiorek / forge
  Basic experiment framework for tensorflow.
  ☆91Updated 4 years ago
• PGM-Lab / probai-2021-pyro
  Repo for the Tutorials of Day1-Day3 of the Nordic Probabilistic AI School 2021 (https://probabilistic.ai/)
  ☆48Updated 3 years ago
• conormdurkan / autoregressive-energy-machines
  Autoregressive Energy Machines
  ☆78Updated 2 years ago
• probabilisticai / probai-2019
  Materials of the Nordic Probabilistic AI School 2019.
  ☆129Updated 5 years ago
• tmlss2018 / PracticalSessions
  ☆123Updated 6 years ago
• rflamary / OTML_DS3_2018
  Practical sessions for the Optimal Transport and Machine learning course at DS3 2018
  ☆90Updated 7 years ago
• facebookresearch / qhoptim
  Implementations of quasi-hyperbolic optimization algorithms.
  ☆102Updated 5 years ago
• Vermeille / Torchelie
  Torchélie is a set of utility functions, layers, losses, models, trainers and other things for PyTorch.
  ☆110Updated 7 months ago
• ganguli-lab / deepchaos
  Experiments for the paper "Exponential expressivity in deep neural networks through transient chaos"
  ☆72Updated 9 years ago
• Scitator / papers
  ☆50Updated 7 years ago
• nicola-decao / BNAF
  Pytorch implementation of Block Neural Autoregressive Flow
  ☆181Updated 3 years ago
• ivannz / mlss2019-bayesian-deep-learning
  MLSS2019 Tutorial on Bayesian Deep Learning
  ☆93Updated 5 years ago
• gbaydin / hypergradient-descent
  Hypergradient descent
  ☆149Updated last year
• team-approx-bayes / dl-with-bayes
  Contains code for the NeurIPS 2019 paper "Practical Deep Learning with Bayesian Principles"
  ☆245Updated 5 years ago
• microsoft / deterministic-variational-inference
  Sample code for running deterministic variational inference to train Bayesian neural networks
  ☆100Updated 6 years ago