team-approx-bayes / ivonLinks
IVON optimizer for neural networks based on variational learning.
☆68Updated 8 months ago
Alternatives and similar repositories for ivon
Users that are interested in ivon are comparing it to the libraries listed below
Sorting:
- PyTorch linear operators for curvature matrices (Hessian, Fisher/GGN, KFAC, ...)☆40Updated 2 months ago
- Sampling with gradient-based Markov Chain Monte Carlo approaches☆103Updated last year
- All You Need is a Good Functional Prior for Bayesian Deep Learning (JMLR 2022)☆20Updated 3 years ago
- Agustinus' very opiniated publication-ready plotting library☆67Updated 2 months ago
- Simple (and cheap!) neural network uncertainty estimation☆66Updated last month
- Laplace approximations for Deep Learning.☆514Updated 2 months ago
- Parameter-Free Optimizers for Pytorch☆130Updated last year
- A general-purpose, deep learning-first library for constrained optimization in PyTorch☆129Updated last month
- Bayesian active learning with EPIG data acquisition☆32Updated 2 months ago
- Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)☆20Updated 6 years ago
- Normalizing Flows with a resampled base distribution☆47Updated 2 years ago
- Code for Gaussian Score Matching Variational Inference☆34Updated 4 months ago
- ☆52Updated 2 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…☆53Updated last year
- Normalizing flows in PyTorch☆396Updated last month
- Posterior Refinement Improves Sample Efficiency in Bayesian Neural Networks☆10Updated 2 years ago
- Repo for the Tutorials of Day1-Day2 of the Nordic Probabilistic AI School 2023☆17Updated 2 years ago
- ☆17Updated 10 months ago
- Code for the paper: "Independent mechanism analysis, a new concept?"☆24Updated 2 years ago
- ☆152Updated 2 years ago
- Algorithms for computations on random manifolds made easier☆91Updated last year
- Sketched matrix decompositions for PyTorch☆70Updated last week
- PyTorch-based library for Riemannian Manifold Hamiltonian Monte Carlo (RMHMC) and inference in Bayesian neural networks☆451Updated 10 months ago
- Code for the paper "Bayesian Neural Network Priors Revisited"☆57Updated 4 years ago
- Laplace Redux -- Effortless Bayesian Deep Learning☆42Updated last month
- Source code for Large-Scale Wasserstein Gradient Flows (NeurIPS 2021)☆33Updated 3 years ago
- Instructions and examples to deploy some PyTorch code on slurm using a Singularity Container☆33Updated 2 years ago
- ☆23Updated last year
- Neural Diffusion Processes☆81Updated 11 months ago
- Repository for the work Transforming Gaussian Processes with Normalizing Flows published at AISTATS 2021☆24Updated 2 years ago