rbardenet / bml-course
Public repo for course material on Bayesian machine learning at ENS Paris-Saclay and Univ Lille
☆86Updated last month
Alternatives and similar repositories for bml-course:
Users that are interested in bml-course are comparing it to the libraries listed below
- Materials of the Nordic Probabilistic AI School 2023.☆91Updated last year
- Bayesianize: A Bayesian neural network wrapper in pytorch☆88Updated 11 months ago
- ☆151Updated 2 years ago
- PyTorch linear operators for curvature matrices (Hessian, Fisher/GGN, KFAC, ...)☆36Updated this week
- Lightweight library of stochastic gradient MCMC algorithms written in JAX.☆103Updated last year
- Repo for the Tutorials of Day1-Day2 of the Nordic Probabilistic AI School 2023☆17Updated last year
- Materials of the Nordic Probabilistic AI School 2022.☆176Updated 2 years ago
- Code for the paper "Bayesian Neural Network Priors Revisited"☆57Updated 3 years ago
- Materials of the Nordic Probabilistic AI School 2021.☆93Updated 3 years ago
- ☆241Updated 2 years ago
- Parameter-Free Optimizers for Pytorch☆122Updated 11 months ago
- Normalizing Flows using JAX☆83Updated last year
- Repo for the Tutorials of Day1-Day3 of the Nordic Probabilistic AI School 2021 (https://probabilistic.ai/)☆48Updated 3 years ago
- A library for uncertainty quantification based on PyTorch☆123Updated 3 years ago
- A community repository for benchmarking Bayesian methods☆110Updated 3 years ago
- Bayesian active learning with EPIG data acquisition☆31Updated this week
- Bayes-Newton—A Gaussian process library in JAX, with a unifying view of approximate Bayesian inference as variants of Newton's method.☆232Updated last year
- Agustinus' very opiniated publication-ready plotting library☆63Updated 2 months ago
- Algorithms for computations on random manifolds made easier☆90Updated last year
- A primer on Bayesian Neural Networks. The aim of this reading list is to facilitate the entry of new researchers into the field of Bayesi…☆52Updated last year
- Approximate inference for Markov Gaussian processes using iterated Kalman smoothing, in JAX☆99Updated last year
- Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)☆20Updated 6 years ago
- Light-weighted code for Orthogonal Additive Gaussian Processes☆42Updated 8 months ago
- Instructions and examples to deploy some PyTorch code on slurm using a Singularity Container☆33Updated 2 years ago
- Repository for the work Transforming Gaussian Processes with Normalizing Flows published at AISTATS 2021☆24Updated 2 years ago
- Manifold-learning flows (ℳ-flows)☆228Updated 4 years ago
- Laplace Redux -- Effortless Bayesian Deep Learning☆43Updated 2 years ago
- Code for "Depth Uncertainty in Neural Networks" (https://arxiv.org/abs/2006.08437)☆75Updated last year
- Simple (and cheap!) neural network uncertainty estimation☆63Updated last week
- This library would form a permanent home for reusable components for deep probabilistic programming. The library would form and harness a…☆306Updated last month