RaulPL / awesome-gaussian-processes
A curated list of resources for learning Gaussian Processes
☆38Updated 3 years ago
Alternatives and similar repositories for awesome-gaussian-processes:
Users that are interested in awesome-gaussian-processes are comparing it to the libraries listed below
- Gaussian Process and Uncertainty Quantification Summer School 2020☆33Updated 2 years ago
- An ultra-lightweight JAX implementation of sparse Gaussian processes via pathwise sampling.☆22Updated 4 years ago
- Tutorial materials of the Probabilistic Numerics Spring School.☆34Updated last year
- Supplementary code for the NeurIPS 2020 paper "Matern Gaussian processes on Riemannian manifolds".☆28Updated 2 months ago
- Library for Bayesian Neural Networks in PyTorch (first version as published in ProbProg2020)☆42Updated 3 years ago
- Tutorials and sampling algorithm comparisons☆72Updated this week
- ☆30Updated 2 years ago
- Code for efficiently sampling functions from GP(flow) posteriors☆72Updated 4 years ago
- Minimal Gaussian process library in JAX with a simple (custom) approach to state management.☆11Updated last year
- Code repo for "Kernel Interpolation for Scalable Online Gaussian Processes"☆60Updated 4 years ago
- A generic interface for linear algebra backends☆73Updated last month
- Approximate inference for Markov Gaussian processes using iterated Kalman smoothing, in JAX☆98Updated last year
- Lightweight library of stochastic gradient MCMC algorithms written in JAX.☆102Updated last year
- Normalizing Flows using JAX☆83Updated last year
- Fully Bayesian Inference in GPs - Gaussian and Generic Likelihoods☆22Updated last year
- Jax SSM Library☆49Updated 2 years ago
- Recursive Bayesian Estimation (Sequential / Online Inference)☆58Updated 11 months ago
- Riemannian Convex Potential Maps☆67Updated 2 years ago
- Bayesian algorithm execution (BAX)☆49Updated 3 years ago
- All things Monte Carlo, written in JAX.☆30Updated 2 years ago
- Source code for my PhD thesis: Backpropagation Beyond the Gradient☆20Updated 2 years ago
- Bayesian inference for a logistic regression model in various languages☆42Updated last year
- IterGP: Computation-Aware Gaussian Process Inference (NeurIPS 2022)☆40Updated last year
- Neat Bayesian machine learning examples☆55Updated 2 months ago
- Sequential Neural Likelihood☆39Updated 5 years ago
- Talks from Neil Lawrence☆54Updated last year
- pyrff: Python implementation of random fourier feature approximations for gaussian processes☆28Updated 2 weeks ago
- Deep Adaptive Design: Amortizing Sequential Bayesian Experimental Design☆31Updated 3 years ago
- A LinearOperator implementation to wrap the numerical nuts and bolts of GPyTorch☆107Updated 3 weeks ago
- A Julia implementation of sparse Gaussian processes via path-wise doubly stochastic variational inference.☆33Updated 4 years ago