Alternatives and similar repositories for lectures:

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

• mlss-skoltech / tutorials
  repository with the tutorials for MLSS Skoltech
  ☆66Updated 5 years ago
• deeppavlov / tdl
  Course "Theories of Deep Learning"
  ☆196Updated 5 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
• RobRomijnders / weight_uncertainty
  Implementing Bayes by Backprop
  ☆183Updated 6 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
• bayesgroup / bayesgroup.github.io
  ☆83Updated last year
• bayesgroup / deepbayes2017
  ☆66Updated 7 years ago
• HolyBayes / pytorch_ard
  Pytorch implementation of Variational Dropout Sparsifies Deep Neural Networks
  ☆83Updated 3 years ago
• deeppavlov / tdl2
  Theoretical Deep Learning: generalization ability
  ☆46Updated 5 years ago
• mlss-2019 / tutorials
  ☆273Updated 4 years ago
• microsoft / deterministic-variational-inference
  Sample code for running deterministic variational inference to train Bayesian neural networks
  ☆100Updated 6 years ago
• xgfs / imd
  Code for MSID, a Multi-Scale Intrinsic Distance for comparing generative models, studying neural networks, and more!
  ☆51Updated 5 years ago
• tmlss2018 / PracticalSessions
  ☆123Updated 6 years ago
• abdulfatir / normalizing-flows
  Understanding normalizing flows
  ☆132Updated 5 years ago
• mblondel / fenchel-young-losses
  Probabilistic classification in PyTorch/TensorFlow/scikit-learn with Fenchel-Young losses
  ☆185Updated last year
• aiwabdn / pygln
  Python implementation of GLN in different frameworks
  ☆98Updated 4 years ago
• ruqizhang / csgmcmc
  Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning
  ☆92Updated 4 years ago
• ivannz / mlss2019-bayesian-deep-learning
  MLSS2019 Tutorial on Bayesian Deep Learning
  ☆91Updated 5 years ago
• joanbruna / MathsDL-spring19
  Mathematics of Deep Learning, Courant Insititute, Spring 19
  ☆275Updated 6 years ago
• probabilisticai / probai-2021
  Materials of the Nordic Probabilistic AI School 2021.
  ☆93Updated 3 years ago
• team-approx-bayes / dl-with-bayes
  Contains code for the NeurIPS 2019 paper "Practical Deep Learning with Bayesian Principles"
  ☆244Updated 5 years ago
• izmailovpavel / understandingbdl
  ☆241Updated 2 years ago
• probabilisticai / probai-2019
  Materials of the Nordic Probabilistic AI School 2019.
  ☆130Updated 4 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, …
  ☆113Updated 6 years ago
• eemlcommunity / PracticalSessions2019
  Materials for the practical sessions at EEML2019
  ☆79Updated 4 years ago
• microsoft / bayesianize
  Bayesianize: A Bayesian neural network wrapper in pytorch
  ☆88Updated 11 months ago
• jxbz / fromage
  🧀 Pytorch code for the Fromage optimiser.
  ☆124Updated 9 months ago
• eemlcommunity / PracticalSessions2021
  ☆62Updated 3 years ago
• SamsungLabs / pytorch-ensembles
  Pitfalls of In-Domain Uncertainty Estimation and Ensembling in Deep Learning, ICLR 2020
  ☆235Updated 2 years ago
• riannevdberg / sylvester-flows
  ☆180Updated 5 years ago