markvdw / GPflow-inter-domainLinks
Gaussian processes in TensorFlow with modifications to allow inter-domain inducing variables
☆13Updated 7 years ago
Alternatives and similar repositories for GPflow-inter-domain
Users that are interested in GPflow-inter-domain are comparing it to the libraries listed below
Sorting:
- Code and data for the paper `Bayesian Semi-supervised Learning with Graph Gaussian Processes'☆38Updated 6 years ago
- Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019☆41Updated 2 years ago
- 🤿 Implementation of doubly stochastic deep Gaussian Process using GPflow and TensorFlow 2.0☆26Updated last year
- Asymmetric Transfer Learning with Deep Gaussian Processes☆18Updated 10 years ago
- learning point processes by means of optimal transport and wasserstein distance☆54Updated 7 years ago
- see https://github.com/thangbui/geepee for a faster implementation☆37Updated 8 years ago
- Gaussian Processes in Pytorch☆75Updated 5 years ago
- Source code for Naesseth et. al. "Reparameterization Gradients through Acceptance-Rejection Sampling Algorithms" (2017)☆39Updated 8 years ago
- Semi supervised learning on graphs☆35Updated 7 years ago
- ☆25Updated 6 years ago
- Deep Gaussian Processes with Doubly Stochastic Variational Inference☆150Updated 6 years ago
- ☆40Updated 6 years ago
- ☆28Updated 6 years ago
- Sample code for running deterministic variational inference to train Bayesian neural networks☆100Updated 6 years ago
- Deep Kernel Learning. Gaussian Process Regression where the input is a neural network mapping of x that maximizes the marginal likelihood☆93Updated 7 years ago
- Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)☆85Updated 4 years ago
- Convolutional Gaussian processes based on GPflow.☆95Updated 7 years ago
- A variational inference method with accurate uncertainty estimation. It uses a new semi-implicit variational family built on neural netwo…☆54Updated 8 months ago
- code release for the NIPS 2016 paper☆27Updated 8 years ago
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 5 years ago
- A Python implementation of Kernel Mean Matching data reweighting algorithm☆32Updated 9 years ago
- Learnable Graph Discovery☆10Updated 6 years ago
- Neural Processes implementation for 1D regression☆65Updated 6 years ago
- [Code] Deep Multi-task Representation Learning: A Tensor Factorisation Approach☆58Updated 8 years ago
- The collection of recent papers about variational inference☆85Updated 5 years ago
- Multiplicative Normalizing Flow (MNF) posteriors for variational Bayesian neural networks☆65Updated 4 years ago
- Code for the paper Implicit Weight Uncertainty in Neural Networks☆65Updated 5 years ago
- Example implementation of the Bayesian neural network in "Structured and Efficient Variational Deep Learning with Matrix Gaussian Posteri…☆30Updated 4 years ago
- Deep convolutional gaussian processes.☆78Updated 5 years ago
- Gaussian processes with PyTorch☆30Updated 3 years ago