IdanAchituve / GDKLLinks
Code that accompanies the paper Guided Deep Kernel Learning
☆10Updated 2 years ago
Alternatives and similar repositories for GDKL
Users that are interested in GDKL are comparing it to the libraries listed below
Sorting:
- Fully Bayesian Inference in GPs - Gaussian and Generic Likelihoods☆22Updated 2 years ago
- Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)☆20Updated 6 years ago
- Code for NeurIPS 2021 paper 'Spatio-Temporal Variational Gaussian Processes'☆47Updated 4 years ago
- A repository with implementations of major papers on Gaussian Process regression models, implemented from scratch in Python, notably incl…☆14Updated 3 years ago
- Non-stationary spectral mixture kernels implemented in GPflow☆28Updated 7 years ago
- Jax SSM Library☆48Updated 3 years ago
- Code for efficiently sampling functions from GP(flow) posteriors☆73Updated 5 years ago
- Repository for the work Transforming Gaussian Processes with Normalizing Flows published at AISTATS 2021☆24Updated 2 years ago
- A framework for composing Neural Processes in Python☆88Updated 11 months ago
- An ultra-lightweight JAX implementation of sparse Gaussian processes via pathwise sampling.☆22Updated 4 years ago
- A variational method for fast, approximate inference for stochastic differential equations.☆45Updated 7 years ago
- Recursive Bayesian Estimation (Sequential / Online Inference)☆60Updated last year
- Exploring how to to deal with uncertain inputs with gaussian process regression models.☆27Updated 4 years ago
- Code for the paper "Bayesian Neural Network Priors Revisited"☆58Updated 4 years ago
- Neat Bayesian machine learning examples☆58Updated this week
- We got a stew going!☆27Updated 2 years ago
- Implementation of stochastic variational inference for differentially deep gaussian processes☆15Updated 7 years ago
- Implementations of Normalizing Flows in Pytorch/Pyro☆18Updated 5 years ago
- Simple, extensible implementations of some meta-learning algorithms in Jax☆10Updated 5 years ago
- ☆15Updated 3 years ago
- Lightweight library of stochastic gradient MCMC algorithms written in JAX.☆105Updated 2 years ago
- Modular Gaussian Processes☆16Updated 3 years ago
- Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances☆50Updated 2 years ago
- Minimal Gaussian process library in JAX with a simple (custom) approach to state management.☆12Updated last year
- Robust initialisation of inducing points in sparse variational GP regression models.☆33Updated 3 years ago
- Public code for running Stochastic Gradient Descent on GPs.☆39Updated 7 months ago
- Implementation of the Gaussian Process Autoregressive Regression Model☆68Updated 10 months ago
- Bayesian Neural Network Surrogates for Bayesian Optimization☆63Updated last year
- beta-NLL introduced in our paper "On the Pitfalls of Heteroscedastic Uncertainty Estimation with Probabilistic Neural Networks" ICLR 2022☆46Updated 3 years ago
- Code repo for "Function-Space Distributions over Kernels"☆32Updated 4 years ago