epfml / opt-summerschool

Related projects ⓘ

Alternatives and complementary repositories for opt-summerschool

• PGM-Lab / probabilisticAI_tutorials
  Repo for the Tutorials of Day1-Day3 of the Nordic Probabilistic AI School 2019 (https://2019.probabilistic.ai/)
  ☆20Updated 5 years ago
• didriknielsen / ds3_abi_exercises
  Exercises for the Tutorial on Approximate Bayesian Inference at the Data Science Summer School 2018
  ☆22Updated 6 years ago
• ermongroup / BiasAndGeneralization
  ☆26Updated 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…
  ☆54Updated 4 years ago
• JeanKossaifi / ifi-summer-school
  Slides and notebooks for the IfI Summer School 2018 on Machine Learning
  ☆36Updated 6 years ago
• epfml / opt-shortcourse
  Short Course on Optimization for Machine Learning - Slides and Practical Lab - Pre-doc Summer School on Learning Systems, July 3 to 7, 20…
  ☆18Updated 7 years ago
• udellgroup / orie7191
  Materials for ORIE 7191: Topics in Optimization for Machine Learning
  ☆42Updated 5 years ago
• sinead / DS32019
  Materials for short course on Bayesian inference at the Data Science Summer School
  ☆13Updated 5 years ago
• lxuechen / BDMC
  PyTorch implementation of Bidirectional Monte Carlo, Annealed Importance Sampling, and Hamiltonian Monte Carlo.
  ☆52Updated 3 years ago
• wjmaddox / drbayes
  Code Repo for "Subspace Inference for Bayesian Deep Learning"
  ☆81Updated 5 months ago
• wjmaddox / spectralgp
  Code repo for "Function-Space Distributions over Kernels"
  ☆31Updated 3 years ago
• AdamCobb / LCBNN
  ☆25Updated 2 years ago
• cambridge-mlg / cnn-gp
  Pytorch version of "Deep Convolutional Networks as shallow Gaussian Processes" by Adrià Garriga-Alonso, Carl Rasmussen and Laurence Aitch…
  ☆32Updated 4 years ago
• pierresegonne / VINF
  Repository for DTU Special Course, focusing on Variational Inference using Normalizing Flows (VINF). Supervised by Michael Riis Andersen
  ☆25Updated 4 years ago
• JeanKossaifi / caltech-tutorial
  Material for my Caltech tutorial on deep learning and tensor methods
  ☆69Updated 6 years ago
• karalets / TyXe
  Library for Bayesian Neural Networks in PyTorch (first version as published in ProbProg2020)
  ☆42Updated 3 years ago
• thangbui / geepee
  A collection of Gaussian process models
  ☆30Updated 7 years ago
• gebob19 / introduction_to_normalizing_flows
  Jupyter Notebook corresponding to 'Going with the Flow: An Introduction to Normalizing Flows'
  ☆25Updated 3 years ago
• KarenUllrich / binary-VAE
  A minimal implementation of a VAE with BinConcrete (relaxed Bernoulli) latent distribution in TensorFlow.
  ☆21Updated 4 years ago
• wittawatj / kernel-gof
  NeurIPS 2017 best paper. An interpretable linear-time kernel goodness-of-fit test.
  ☆67Updated 5 years ago
• lwehbe / 10606607_M20
  ☆14Updated 4 years ago
• ssydasheng / Neural-Kernel-Network
  Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326
  ☆71Updated 6 years ago
• jxbz / madam
  👩 Pytorch and Jax code for the Madam optimiser.
  ☆51Updated 3 years ago
• thegregyang / NNspectra
  Computing the eigenvalues of Neural Tangent Kernel and Conjugate Kernel (aka NNGP kernel) over the boolean cube
  ☆47Updated 5 years ago
• chrisorm / pydata-2018
  ☆63Updated 6 years ago
• cunningham-lab / cb_and_cc
  ☆36Updated last year
• franrruiz / uivi
  Code for Unbiased Implicit Variational Inference (UIVI)
  ☆13Updated 5 years ago
• jameshensman / VFF
  Variational Fourier Features
  ☆83Updated 3 years ago
• mauriziofilippone / deep_gp_random_features
  ☆40Updated 5 years ago
• gkdziugaite / pacbayes-opt
  Optimizing PAC-Bayes bounds for Stochastic Neural Networks with Gaussian weights
  ☆26Updated 4 years ago