Repository for the paper "Riemannian Laplace approximations for Bayesian neural networks"
☆13Dec 24, 2023Updated 2 years ago
Alternatives and similar repositories for riemannian-laplace-approximation
Users that are interested in riemannian-laplace-approximation are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- Posterior Refinement Improves Sample Efficiency in Bayesian Neural Networks☆11Oct 21, 2022Updated 3 years ago
- Repositório para disponibilizar o material feito pelos monitores da disciplina de Álgebra Linear da EMAp.☆28Nov 17, 2021Updated 4 years ago
- ☆34Aug 30, 2022Updated 4 years ago
- A Metropolis-Hastings MCMC sampler accelerated via diffusion models☆18Jul 25, 2024Updated 2 years ago
- Generative Uncertainty in Diffusion Models☆16Jun 23, 2025Updated last year
- Deploy open-source AI quickly and easily - Special Bonus Offer • AdRunpod Hub is built for open source. One-click deployment and autoscaling endpoints without provisioning your own infrastructure.
- Minimal (unofficial) implementation of the flow map matching method.☆16Jul 9, 2025Updated last year
- Modular Gaussian Processes☆17Dec 9, 2021Updated 4 years ago
- Improving Adversarial Robustness via Mutual Information Estimation☆11Apr 2, 2024Updated 2 years ago
- ☆12Jun 5, 2015Updated 11 years ago
- This repository contains code for applying Riemannian geometry in machine learning.☆80Jun 21, 2021Updated 5 years ago
- ☆21Apr 8, 2020Updated 6 years ago
- Vivacious terminal windows for Jupyter Book and Sphinx.☆10Jul 1, 2021Updated 5 years ago
- A crash course in diffusion-based models☆15Aug 19, 2025Updated last year
- Code for Gaussian Score Matching Variational Inference☆34Feb 23, 2025Updated last year
- Serverless GPU API endpoints on Runpod - Get Bonus Credits • AdSkip the infrastructure headaches. Auto-scaling, pay-as-you-go, no-ops approach lets you focus on innovating your application.
- Code of "A Geometric Perspective on Variational Autoencoders" (NeurIPS 2022)☆16Nov 19, 2024Updated last year
- Bayesian active learning with EPIG data acquisition☆42Sep 4, 2025Updated last year
- Curso de introdução à computação☆48May 29, 2026Updated 4 months ago
- Repository for the workshop "Latent space navigation – interpretation, probing and steering" organized at Danish Digitalization, Data Sci…☆22Aug 26, 2025Updated last year
- ☆20Dec 13, 2023Updated 2 years ago
- Visualize neural networks using TikZ in Julia☆15Jan 29, 2025Updated last year
- This repository contains the code used in a publication 'Active Learning for Decision-Making from Imbalanced Observational Data', Iiris S…☆11May 14, 2019Updated 7 years ago
- CIFAR10 ResNets implemented in JAX+Flax☆12Apr 6, 2022Updated 4 years ago
- ICML23 "Latent Traversals in Generative Models as Potential Flows"☆28Oct 23, 2023Updated 2 years ago
- End-to-end encrypted email - Proton Mail • AdSpecial offer: 40% Off Yearly / 80% Off First Month. All Proton services are open source and independently audited for security.
- A Wavenet Primer. From audio preparation to audio generation.☆42Nov 7, 2020Updated 5 years ago
- CEVAE with VampPrior☆11Jul 18, 2018Updated 8 years ago
- All You Need is a Good Functional Prior for Bayesian Deep Learning (JMLR 2022)☆19Apr 22, 2022Updated 4 years ago
- Advanced course on Reinforcement Learning.☆45Oct 28, 2025Updated 11 months ago
- Quantile Local Projections☆12Aug 8, 2022Updated 4 years ago
- A collection of tensor completion algorithms☆26Apr 18, 2021Updated 5 years ago
- ☆16Apr 26, 2023Updated 3 years ago
- Algorithms for computations on random manifolds made easier☆101Dec 4, 2023Updated 2 years ago
- [NeurIPS 2020] Task-Agnostic Amortized Inference of Gaussian Process Hyperparameters (AHGP)☆23Dec 9, 2020Updated 5 years ago
- Deploy on Railway without the complexity - Free Credits Offer • AdConnect your repo and Railway handles the rest with instant previews. Quickly provision container image services, databases, and storage volumes.
- Quantile-based Spectral Analysis of Time Series☆13Jul 10, 2024Updated 2 years ago
- ☆25Nov 2, 2022Updated 3 years ago
- Free-form flows are a generative model training a pair of neural networks via maximum likelihood☆51Jun 26, 2025Updated last year
- Lambert W function and Lambert W x F distributions in pytorch☆17Aug 11, 2025Updated last year
- Sparse Orthogonal Variational Inference for Gaussian Processes (SOLVE-GP)☆23Jun 22, 2021Updated 5 years ago
- Concrete Dropout implementation for Tensorflow 2.0 and PyTorch☆14Dec 18, 2024Updated last year
- RIMD: Efficient and Flexible Deformation Representation for Data-Driven Surface Modeling (Siggraph 2016)☆11Mar 28, 2020Updated 6 years ago