GAMES-UChile / The_Art_of_Gaussian_ProcessesLinks
☆39Updated 3 years ago
Alternatives and similar repositories for The_Art_of_Gaussian_Processes
Users that are interested in The_Art_of_Gaussian_Processes are comparing it to the libraries listed below
Sorting:
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆49Updated 5 years ago
- ☆251Updated 2 years ago
- AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'☆90Updated 5 years ago
- Implementation of the Functional Neural Process models☆42Updated 5 years ago
- Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"☆33Updated 3 years ago
- Repository for theory and methods for Out-of-Distribution (OoD) generalization☆63Updated 3 years ago
- This repository contains code for applying Riemannian geometry in machine learning.☆78Updated 4 years ago
- ☆54Updated last year
- Code Repo for "Subspace Inference for Bayesian Deep Learning"☆83Updated last year
- Contains code for the NeurIPS 2020 paper by Pan et al., "Continual Deep Learning by FunctionalRegularisation of Memorable Past"☆44Updated 5 years ago
- Code for the paper "Bayesian Neural Network Priors Revisited"☆58Updated 4 years ago
- ☆67Updated 6 years ago
- Code for A General Recipe for Likelihood-free Bayesian Optimization, ICML 2022☆45Updated 3 years ago
- Sample code for running deterministic variational inference to train Bayesian neural networks☆100Updated 7 years ago
- Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)☆85Updated 5 years ago
- Pytorch implementation of Neural Processes for functions and images☆234Updated 3 years ago
- PyTorch implementation of Stein Variational Gradient Descent☆46Updated 2 years ago
- ☆37Updated 5 years ago
- The collection of recent papers about variational inference☆84Updated 6 years ago
- Codebase for Learning Invariances in Neural Networks☆96Updated 3 years ago
- Code for "Bayesian Structure Learning with Generative Flow Networks"☆93Updated 3 years ago
- Learning error bars for neural network predictions☆72Updated 5 years ago
- The codebase for the paper "A Tail-Index Analysis of Stochastic Gradient Noise in Deep Neural Networks"☆25Updated 6 years ago
- Code for "Depth Uncertainty in Neural Networks" (https://arxiv.org/abs/2006.08437)☆78Updated 2 years ago
- ☆124Updated last year
- Official repository for "Categorical Normalizing Flows via Continuous Transformations"☆57Updated 4 years ago
- Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning☆93Updated 5 years ago
- Code for "On Feature Collapse and Deep Kernel Learning for Single Forward Pass Uncertainty".☆114Updated 3 years ago
- {KFAC,EKFAC,Diagonal,Implicit} Fisher Matrices and finite width NTKs in PyTorch☆215Updated 2 weeks ago
- Code for the paper: "Independent mechanism analysis, a new concept?"☆24Updated 2 years ago