IdanAchituve / GDKL
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
- Fully Bayesian Inference in GPs - Gaussian and Generic Likelihoods☆22Updated last year
- ☆15Updated 2 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
- Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)☆20Updated 5 years ago
- Non-stationary spectral mixture kernels implemented in GPflow☆28Updated 6 years ago
- Implicit Deep Adaptive Design (iDAD): Policy-Based Experimental Design without Likelihoods☆19Updated 3 years ago
- Posterior Refinement Improves Sample Efficiency in Bayesian Neural Networks☆10Updated 2 years ago
- Repository for the work Transforming Gaussian Processes with Normalizing Flows published at AISTATS 2021☆24Updated 2 years ago
- Bayesian active learning with EPIG data acquisition☆28Updated last month
- Improving predictions of Bayesian neural nets via local linearization, AISTATS 2021☆17Updated 2 years ago
- ☆13Updated last year
- An ultra-lightweight JAX implementation of sparse Gaussian processes via pathwise sampling.☆22Updated 3 years ago
- Modular Gaussian Processes☆15Updated 3 years ago
- Light-weighted code for Orthogonal Additive Gaussian Processes☆41Updated 7 months ago
- Simple (and cheap!) neural network uncertainty estimation☆61Updated last month
- Code for NeurIPS 2021 paper 'Spatio-Temporal Variational Gaussian Processes'☆47Updated 3 years ago
- All You Need is a Good Functional Prior for Bayesian Deep Learning (JMLR 2022)☆21Updated 2 years ago
- Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"☆33Updated 2 years ago
- A Tensorflow based library for Time Series Modelling with Gaussian Processes☆29Updated 8 months ago
- Laplace Redux -- Effortless Bayesian Deep Learning☆42Updated last year
- Bayesian Neural Network Surrogates for Bayesian Optimization☆48Updated 10 months ago
- Implementations of Normalizing Flows in Pytorch/Pyro☆19Updated 4 years ago
- Implementation of stochastic variational inference for differentially deep gaussian processes☆15Updated 6 years ago
- We got a stew going!☆27Updated last year
- Code repo for "Function-Space Distributions over Kernels"☆31Updated 4 years ago
- Code for the paper "Bayesian Neural Network Priors Revisited"☆58Updated 3 years ago
- Minimal Gaussian process library in JAX with a simple (custom) approach to state management.☆11Updated last year
- Implementation for Non-stationary Spectral Kernels (NIPS 2017)☆20Updated 5 years ago
- Methods and experiments for assumed density SDE approximations☆11Updated 3 years ago
- simple JAX-/NumPy-based implementations of NGD with exact/approximate Fisher Information Matrix both in parameter-space and function-spac…☆14Updated 4 years ago