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
- Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)☆20Updated 5 years ago
- ☆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
- Posterior Refinement Improves Sample Efficiency in Bayesian Neural Networks☆9Updated 2 years ago
- A Tensorflow based library for Time Series Modelling with Gaussian Processes☆29Updated 7 months ago
- Non-stationary spectral mixture kernels implemented in GPflow☆28Updated 6 years ago
- An ultra-lightweight JAX implementation of sparse Gaussian processes via pathwise sampling.☆22Updated 3 years ago
- Laplace Redux -- Effortless Bayesian Deep Learning☆41Updated last year
- Light-weighted code for Orthogonal Additive Gaussian Processes☆41Updated 6 months ago
- Vector Quantile Regression☆19Updated last year
- Bayesian active learning with EPIG data acquisition☆27Updated last week
- Code repo for "Function-Space Distributions over Kernels"☆31Updated 4 years ago
- A library implementing the kernels for and experiments using extrinsic gauge equivariant vector field Gaussian Processes☆25Updated 3 years ago
- ☆20Updated 10 months ago
- Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"☆33Updated 2 years ago
- ☆13Updated last year
- Repository for the work Transforming Gaussian Processes with Normalizing Flows published at AISTATS 2021☆23Updated 2 years ago
- Modular Gaussian Processes☆15Updated 3 years ago
- Simple (and cheap!) neural network uncertainty estimation☆61Updated this week
- Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances☆46Updated last year
- Implementation for Non-stationary Spectral Kernels (NIPS 2017)☆20Updated 5 years ago
- Repository for DTU Special Course, focusing on Variational Inference using Normalizing Flows (VINF). Supervised by Michael Riis Andersen☆25Updated 4 years ago
- "How to Trust Your Diffusion Models: A Convex Optimization Approach to Conformal Risk Control"☆17Updated last year
- Repo for our paper "Repulsive deep ensembles are Bayesian"☆19Updated 3 years ago
- Code for the paper "Bayesian Neural Network Priors Revisited"☆56Updated 3 years ago
- Public code for running Stochastic Gradient Descent on GPs.☆36Updated 3 months ago
- Official code for the ICLR 2021 paper Neural ODE Processes☆70Updated 2 years ago
- Improving predictions of Bayesian neural nets via local linearization, AISTATS 2021☆17Updated 2 years ago
- Implementation of the Gaussian Process Autoregressive Regression Model☆62Updated 3 weeks ago