IdanAchituve / GDKLLinks
Code that accompanies the paper Guided Deep Kernel Learning
☆10Updated last year
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 last year
- ☆15Updated 2 years ago
- Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)☆20Updated 6 years ago
- Methods and experiments for assumed density SDE approximations☆12Updated 3 years ago
- Modular Gaussian Processes☆15Updated 3 years ago
- Bayesian active learning with EPIG data acquisition☆32Updated last month
- Posterior Refinement Improves Sample Efficiency in Bayesian Neural Networks☆10Updated 2 years ago
- Non-stationary spectral mixture kernels implemented in GPflow☆28Updated 6 years ago
- Laplace Redux -- Effortless Bayesian Deep Learning☆42Updated 2 years ago
- Repo for our paper "Repulsive deep ensembles are Bayesian"☆19Updated 3 years ago
- Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances☆47Updated 2 years ago
- An ultra-lightweight JAX implementation of sparse Gaussian processes via pathwise sampling.☆22Updated 4 years ago
- A repository with implementations of major papers on Gaussian Process regression models, implemented from scratch in Python, notably incl…☆14Updated 2 years ago
- Improving predictions of Bayesian neural nets via local linearization, AISTATS 2021☆17Updated 2 years ago
- Code repo for "Function-Space Distributions over Kernels"☆31Updated 4 years ago
- Stochastic Gradient Langevin Dynamics for Bayesian learning☆31Updated 3 years ago
- Repository for DTU Special Course, focusing on Variational Inference using Normalizing Flows (VINF). Supervised by Michael Riis Andersen☆25Updated 4 years ago
- Random feature latent variable models in Python☆22Updated last year
- Repository for the work Transforming Gaussian Processes with Normalizing Flows published at AISTATS 2021☆24Updated 2 years ago
- Vector Quantile Regression☆19Updated 2 months ago
- A Tensorflow based library for Time Series Modelling with Gaussian Processes☆32Updated 11 months ago
- Implicit Deep Adaptive Design (iDAD): Policy-Based Experimental Design without Likelihoods☆19Updated 3 years ago
- Code for NeurIPS 2021 paper 'Spatio-Temporal Variational Gaussian Processes'☆47Updated 3 years ago
- Minimal Gaussian process library in JAX with a simple (custom) approach to state management.☆12Updated last year
- All You Need is a Good Functional Prior for Bayesian Deep Learning (JMLR 2022)☆21Updated 3 years ago
- Implementation of the Gaussian Process Autoregressive Regression Model☆66Updated 4 months ago
- Light-weighted code for Orthogonal Additive Gaussian Processes☆42Updated 10 months ago
- Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'☆26Updated 4 years ago
- Implementation for Non-stationary Spectral Kernels (NIPS 2017)☆20Updated 5 years ago
- Official code for the ICLR 2021 paper Neural ODE Processes☆72Updated 3 years ago