duvenaud / additive-gpsLinks
Source for experiments in the Additive Gaussian process paper, as well as extensions relating to dropout.
☆21Updated 11 years ago
Alternatives and similar repositories for additive-gps
Users that are interested in additive-gps are comparing it to the libraries listed below
Sorting:
- Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)☆65Updated 6 years ago
- Non-stationary spectral mixture kernels implemented in GPflow☆28Updated 6 years ago
- Code repo for "Function-Space Distributions over Kernels"☆32Updated 4 years ago
- Supplementary code for the NeurIPS 2020 paper "Matern Gaussian processes on Riemannian manifolds".☆29Updated 8 months ago
- Deep Gaussian Processes with Importance-Weighted Variational Inference☆39Updated 6 years ago
- OxCSML research group reading groups and meetings at the Department of Statistics, University of Oxford.☆93Updated 3 years ago
- Library for Bayesian Quadrature☆32Updated 6 years ago
- ☆37Updated 5 years ago
- Deep Gaussian Processes with Doubly Stochastic Variational Inference☆151Updated 6 years ago
- Code for efficiently sampling functions from GP(flow) posteriors☆73Updated 4 years ago
- Nonparametric Differential Equation Modeling☆55Updated last year
- Code to minimize the Variational Contrastive Divergence (VCD)☆29Updated 6 years ago
- Code required to reproduce the experiments in Auxiliary Variational MCMC☆17Updated 7 years ago
- Code for Randomly Projected Additive Gaussian Processes☆25Updated 5 years ago
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 5 years ago
- A community repository for benchmarking Bayesian methods☆110Updated 3 years ago
- Talks from Neil Lawrence☆54Updated last year
- Tensorflow implementation of Stein Variational Gradient Descent (SVGD)☆26Updated 7 years ago
- Code for density estimation with nonparametric cluster shapes.☆39Updated 9 years ago
- TensorFlow implementation for training MCMC samplers from the paper: Generalizing Hamiltonian Monte Carlo with Neural Network☆183Updated 7 years ago
- Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)☆85Updated 5 years ago
- Exercises for the Tutorial on Approximate Bayesian Inference at the Data Science Summer School 2018☆22Updated 7 years ago
- Implementation of GPLVM and Bayesian GPLVM in pytorch/gpytorch☆15Updated 4 years ago
- Deep Adaptive Design: Amortizing Sequential Bayesian Experimental Design☆37Updated 4 years ago
- Variational Fourier Features☆85Updated 4 years ago
- Library for Bayesian Neural Networks in PyTorch (first version as published in ProbProg2020)☆42Updated 4 years ago
- Bayesian Deep Learning with Stochastic Gradient MCMC Methods☆38Updated 4 years ago
- Know Your Boundaries: Constraining Gaussian Processes by Variational Harmonic Features☆24Updated 6 years ago
- ☆51Updated last year
- Convolutional Gaussian processes based on GPflow.☆95Updated 7 years ago