Alternatives and similar repositories for slides:

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

• mlss-2019 / tutorials
  ☆273Updated 4 years ago
• joanbruna / MathsDL-spring19
  Mathematics of Deep Learning, Courant Insititute, Spring 19
  ☆275Updated 6 years ago
• otokonoko8 / deep-Bayesian-nonparametrics-papers
  The collection of papers about combining deep learning and Bayesian nonparametrics
  ☆120Updated 5 years ago
• wiseodd / probabilistic-models
  Collection of probabilistic models and inference algorithms
  ☆241Updated 5 years ago
• ivannz / mlss2019-bayesian-deep-learning
  MLSS2019 Tutorial on Bayesian Deep Learning
  ☆91Updated 5 years ago
• bayesgroup / deepbayes-2019
  Practical assignments of the Deep|Bayes summer school 2019
  ☆830Updated 4 years ago
• rmgarnett / cse515t
  Materials for Bayesian Methods in Machine Learning Course
  ☆88Updated 4 months ago
• abdulfatir / normalizing-flows
  Understanding normalizing flows
  ☆131Updated 5 years ago
• dimenwarper / awesome-bayes
  List of resources for bayesian inference
  ☆154Updated 5 years ago
• sangwoomo / ml-resources
  Personal and biased selection of ML resources
  ☆148Updated 5 years ago
• mcgrady20150318 / BayesianNeuralNetwork
  a repo sharing Bayesian Neural Network recent papers
  ☆216Updated 5 years ago
• robi56 / awesome-bayesian-deep-learning
  A curated list of resources dedicated to bayesian deep learning
  ☆415Updated 7 years ago
• ee227c / ee227c.github.io
  EE227C (Spring 2018) Course page
  ☆224Updated 4 years ago
• bamos / thesis
  Differentiable Optimization-Based Modeling for Machine Learning
  ☆334Updated 5 years ago
• joanbruna / MathsDL-spring18
  Topics course Mathematics of Deep Learning, NYU, Spring 18
  ☆541Updated 2 years ago
• percyliang / cs229t
  Statistical Learning Theory (CS229T) Lecture Notes
  ☆717Updated 5 years ago
• ks838 / Murphy-Machine-Learning-A-Probabilistic-Perspective-Errata-and-Notes-4th-printing
  Murphy's Machine Learning: A Probabilistic Perspective Errata (4th and later printings)
  ☆68Updated 5 years ago
• OATML / bdl-benchmarks
  Bayesian Deep Learning Benchmarks
  ☆670Updated 2 years ago
• t-vi / candlegp
  Gaussian Processes in Pytorch
  ☆75Updated 5 years ago
• Atcold / SP19-DL-collaborative-notes
  Collaborative lecture notes for Spring '19 NYU DL class
  ☆119Updated 5 years ago
• JeanKossaifi / caltech-tutorial
  Material for my Caltech tutorial on deep learning and tensor methods
  ☆70Updated 6 years ago
• microsoft / deterministic-variational-inference
  Sample code for running deterministic variational inference to train Bayesian neural networks
  ☆100Updated 6 years ago
• leopd / geometric-intuition
  Understanding ML and deep learning through geometry
  ☆157Updated 3 years ago
• ssydasheng / Bayesian_neural_network_papers
  Papers for Bayesian-NN
  ☆322Updated 5 years ago
• ctallec / pyvarinf
  Python package facilitating the use of Bayesian Deep Learning methods with Variational Inference for PyTorch
  ☆359Updated 5 years ago
• otokonoko8 / implicit-variational-inference
  The collection of recent papers about variational inference
  ☆85Updated 5 years ago
• wujian16 / Cornell-MOE
  A Python library for the state-of-the-art Bayesian optimization algorithms, with the core implemented in C++.
  ☆268Updated 5 years ago
• pukkapies / dl-imperial-maths
  Code and assignment repository for the Imperial College Mathematics department Deep Learning course
  ☆263Updated 6 years ago
• probabilisticai / probai-2019
  Materials of the Nordic Probabilistic AI School 2019.
  ☆129Updated 4 years ago
• reproducibility-challenge / iclr_2019
  ICLR Reproducibility Challenge 2019
  ☆219Updated 5 years ago