markvdw / RobustGPLinks
Robust initialisation of inducing points in sparse variational GP regression models.
☆34Updated 3 years ago
Alternatives and similar repositories for RobustGP
Users that are interested in RobustGP are comparing it to the libraries listed below
Sorting:
- Implementation of the Gaussian Process Autoregressive Regression Model☆71Updated last year
- Code for efficiently sampling functions from GP(flow) posteriors☆74Updated 5 years ago
- Bayes-Newton—A Gaussian process library in JAX, with a unifying view of approximate Bayesian inference as variants of Newton's method.☆241Updated 2 years ago
- A community repository for benchmarking Bayesian methods☆112Updated 4 years ago
- Light-weighted code for Orthogonal Additive Gaussian Processes☆45Updated last year
- ☆156Updated 3 years ago
- Lightweight library of stochastic gradient MCMC algorithms written in JAX.☆105Updated 2 years ago
- Code for the paper "Bayesian Neural Network Priors Revisited"☆60Updated 4 years ago
- Continual Gaussian Processes☆31Updated 2 years ago
- Non-stationary spectral mixture kernels implemented in GPflow☆28Updated 7 years ago
- An ultra-lightweight JAX implementation of sparse Gaussian processes via pathwise sampling.☆22Updated 4 years ago
- Code repo for "Function-Space Distributions over Kernels"☆32Updated 5 years ago
- 🤿 Implementation of doubly stochastic deep Gaussian Process using GPflow and TensorFlow 2.0☆25Updated last year
- Deep GPs built on top of TensorFlow/Keras and GPflow☆128Updated last year
- Nonparametric Differential Equation Modeling☆56Updated last year
- Simulation-based inference benchmark☆108Updated last year
- Gaussian Processes for Sequential Data☆19Updated 5 years ago
- Code for "Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations"☆172Updated 3 years ago
- Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)☆66Updated 6 years ago
- Recyclable Gaussian Processes☆11Updated 3 years ago
- Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances☆50Updated 2 years ago
- A Tensorflow based library for Time Series Modelling with Gaussian Processes☆32Updated last year
- Approximate inference for Markov Gaussian processes using iterated Kalman smoothing, in JAX☆103Updated 2 years ago
- Deep Gaussian Processes with Importance-Weighted Variational Inference☆39Updated 6 years ago
- Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)☆20Updated 6 years ago
- Source code for my PhD thesis: Backpropagation Beyond the Gradient☆20Updated 2 years ago
- Sequential Neural Likelihood☆42Updated 6 years ago
- Library for Bayesian Neural Networks in PyTorch (first version as published in ProbProg2020)☆42Updated 4 years ago
- Neural likelihood-free methods in PyTorch.☆39Updated 5 years ago
- Conditional density estimation with neural networks☆35Updated last year