j-wilson / GPflowSamplingLinks
Code for efficiently sampling functions from GP(flow) posteriors
☆72Updated 4 years ago
Alternatives and similar repositories for GPflowSampling
Users that are interested in GPflowSampling are comparing it to the libraries listed below
Sorting:
- Nonparametric Differential Equation Modeling☆54Updated last year
- Deep GPs built on top of TensorFlow/Keras and GPflow☆127Updated 9 months ago
- Code repo for "Kernel Interpolation for Scalable Online Gaussian Processes"☆64Updated 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.☆234Updated last year
- Code for "Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations"☆171Updated 3 years ago
- Extensible Tensorflow library for differentiable particle filtering. ICML 2021.☆42Updated 2 years ago
- A community repository for benchmarking Bayesian methods☆110Updated 3 years ago
- Non-stationary spectral mixture kernels implemented in GPflow☆28Updated 6 years ago
- Lightweight library of stochastic gradient MCMC algorithms written in JAX.☆104Updated last year
- Normalizing Flows using JAX☆84Updated last year
- Bayesian Neural Network Surrogates for Bayesian Optimization☆53Updated last year
- Minimal Gaussian process library in JAX with a simple (custom) approach to state management.☆12Updated last year
- Approximate inference for Markov Gaussian processes using iterated Kalman smoothing, in JAX☆100Updated 2 years ago
- Supplementary code for the NeurIPS 2020 paper "Matern Gaussian processes on Riemannian manifolds".☆29Updated 6 months ago
- Simulation-based inference benchmark☆99Updated 6 months ago
- A LinearOperator implementation to wrap the numerical nuts and bolts of GPyTorch☆112Updated 4 months ago
- ☆110Updated 4 years ago
- A generic interface for linear algebra backends☆73Updated 5 months ago
- Implementation of stochastic variational inference for differentially deep gaussian processes☆15Updated 6 years ago
- ☆52Updated 2 years ago
- Repository for the work Transforming Gaussian Processes with Normalizing Flows published at AISTATS 2021☆24Updated 2 years ago
- Light-weighted code for Orthogonal Additive Gaussian Processes☆43Updated last year
- Lightweight MCMC sampling for PyTorch Models aka My Corona Project☆48Updated last week
- Neural likelihood-free methods in PyTorch.☆39Updated 5 years ago
- Sequential Neural Likelihood☆40Updated 5 years ago
- Library for Bayesian Quadrature☆32Updated 6 years ago
- Normalizing Flows with a resampled base distribution☆47Updated 2 years ago
- Code repo for "Function-Space Distributions over Kernels"☆32Updated 4 years ago
- ☆151Updated 2 years ago
- Implicit Deep Adaptive Design (iDAD): Policy-Based Experimental Design without Likelihoods☆20Updated 3 years ago