TyXe-BDL / TyXeLinks
☆155Updated 3 years ago
Alternatives and similar repositories for TyXe
Users that are interested in TyXe are comparing it to the libraries listed below
Sorting:
- Deep GPs built on top of TensorFlow/Keras and GPflow☆127Updated last year
- PyTorch-based library for Riemannian Manifold Hamiltonian Monte Carlo (RMHMC) and inference in Bayesian neural networks☆465Updated last year
- Code for the paper "Bayesian Neural Network Priors Revisited"☆58Updated 4 years ago
- Bayes-Newton—A Gaussian process library in JAX, with a unifying view of approximate Bayesian inference as variants of Newton's method.☆240Updated last year
- Lightweight library of stochastic gradient MCMC algorithms written in JAX.☆105Updated 2 years ago
- Light-weighted code for Orthogonal Additive Gaussian Processes☆43Updated last year
- A library for uncertainty quantification based on PyTorch☆122Updated 3 years ago
- Code for the Neural Processes website and replication of 4 papers on NPs. Pytorch implementation.☆227Updated last year
- Regression datasets from the UCI repository with standardized test-train splits.☆49Updated 3 years ago
- Repository for the work Transforming Gaussian Processes with Normalizing Flows published at AISTATS 2021☆24Updated 2 years ago
- Package implementing various parametric and nonparametric methods for conditional density estimation☆197Updated 2 years ago
- Official Implementation of "Transformers Can Do Bayesian Inference", the PFN paper☆240Updated last year
- Laplace Redux -- Effortless Bayesian Deep Learning☆44Updated 5 months ago
- Simple (and cheap!) neural network uncertainty estimation☆77Updated last month
- Library for Bayesian Neural Networks in PyTorch (first version as published in ProbProg2020)☆42Updated 4 years ago
- Code for efficiently sampling functions from GP(flow) posteriors☆73Updated 5 years ago
- Materials of the Nordic Probabilistic AI School 2022.☆180Updated 3 years ago
- AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'☆90Updated 5 years ago
- Code for "Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations"☆171Updated 3 years ago
- Gaussian process modelling in Python☆225Updated 11 months ago
- A community repository for benchmarking Bayesian methods☆112Updated 4 years ago
- Bayesian active learning with EPIG data acquisition☆35Updated 2 months ago
- Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances☆50Updated 2 years ago
- Manifold-learning flows (ℳ-flows)☆231Updated 5 years ago
- Robust initialisation of inducing points in sparse variational GP regression models.☆33Updated 3 years ago
- Bayesian Neural Network Surrogates for Bayesian Optimization☆63Updated last year
- Public repo for course material on Bayesian machine learning at ENS Paris-Saclay and Univ Lille☆92Updated 9 months ago
- Laplace approximations for Deep Learning.☆527Updated 7 months ago
- Normalizing Flows using JAX☆85Updated 2 years ago
- Normalizing Flows with a resampled base distribution☆47Updated 3 years ago