team-approx-bayes / ivon
IVON optimizer for neural networks based on variational learning.
☆58Updated 2 months ago
Alternatives and similar repositories for ivon:
Users that are interested in ivon are comparing it to the libraries listed below
- Sampling with gradient-based Markov Chain Monte Carlo approaches☆97Updated 9 months ago
- PyTorch linear operators for curvature matrices (Hessian, Fisher/GGN, KFAC, ...)☆25Updated last week
- Lightweight library of stochastic gradient MCMC algorithms written in JAX.☆99Updated last year
- All You Need is a Good Functional Prior for Bayesian Deep Learning (JMLR 2022)☆21Updated 2 years ago
- Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)☆20Updated 5 years ago
- Simple (and cheap!) neural network uncertainty estimation☆60Updated this week
- A LinearOperator implementation to wrap the numerical nuts and bolts of GPyTorch☆100Updated this week
- Code for Gaussian Score Matching Variational Inference☆30Updated 3 months ago
- ☆46Updated last week
- Hessian spectral density estimation in TF and Jax☆120Updated 4 years ago
- Bayesian active learning with EPIG data acquisition☆26Updated 3 weeks ago
- ☆134Updated last month
- Code for the paper: "Independent mechanism analysis, a new concept?"☆24Updated last year
- Transformers with doubly stochastic attention☆44Updated 2 years ago
- Normalizing Flows using JAX☆82Updated last year
- Sketched matrix decompositions for PyTorch☆69Updated this week
- Laplace Redux -- Effortless Bayesian Deep Learning☆41Updated last year
- Repo for our paper "Repulsive deep ensembles are Bayesian"☆19Updated 3 years ago
- 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
- Algorithms for computations on random manifolds made easier☆87Updated last year
- Instructions and examples to deploy some PyTorch code on slurm using a Singularity Container☆33Updated last year
- ☆49Updated last year
- A PyTorch re-implementation of "Doubly Reparameterized Gradient Estimators for Monte Carlo Objectives"☆18Updated 5 years ago
- Posterior Refinement Improves Sample Efficiency in Bayesian Neural Networks☆9Updated 2 years ago
- Code for our paper: Online Variational Filtering and Parameter Learning☆18Updated 3 years ago
- ASDL: Automatic Second-order Differentiation Library for PyTorch☆182Updated last month
- This repository contains code for applying Riemannian geometry in machine learning.☆77Updated 3 years ago
- Tutorial materials of the Probabilistic Numerics Spring School.☆34Updated last year
- Implicit Deep Adaptive Design (iDAD): Policy-Based Experimental Design without Likelihoods☆17Updated 3 years ago
- ☆15Updated 4 months ago