Deep Gaussian Processes with Doubly Stochastic Variational Inference
β153Feb 21, 2019Updated 7 years ago
Alternatives and similar repositories for Doubly-Stochastic-DGP
Users that are interested in Doubly-Stochastic-DGP are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- Deep Gaussian Processes in Pythonβ232Updated this week
- π€Ώ Implementation of doubly stochastic deep Gaussian Process using GPflow and TensorFlow 2.0β25Feb 11, 2024Updated 2 years ago
- β28Feb 15, 2019Updated 7 years ago
- Deep Gaussian Processes with Importance-Weighted Variational Inferenceβ37May 30, 2019Updated 7 years ago
- Variational Fourier Featuresβ88Jun 16, 2021Updated 5 years ago
- Managed hosting for WordPress and PHP on Cloudways β’ AdManaged hosting for WordPress, Magento, Laravel, or PHP apps, on multiple cloud providers. Deploy in minutes on Cloudways by DigitalOcean.
- Deep Gaussian Processes in matlabβ93Sep 14, 2021Updated 5 years ago
- A collection of Gaussian process modelsβ30Aug 17, 2017Updated 9 years ago
- see https://github.com/thangbui/geepee for a faster implementationβ37May 30, 2017Updated 9 years ago
- Library for Deep Gaussian Processes based on GPflowβ18Mar 31, 2020Updated 6 years ago
- Deep convolutional gaussian processes.β82Sep 4, 2019Updated 7 years ago
- Gaussian processes in TensorFlowβ1,921Updated this week
- Convolutional Gaussian processes based on GPflow.β95Oct 31, 2017Updated 8 years ago
- Gaussian processes framework in pythonβ2,168Updated this week
- β26May 15, 2018Updated 8 years ago
- Virtual machines for every use case on DigitalOcean β’ AdGet dependable uptime with 99.99% SLA, simple security tools, and predictable monthly pricing with DigitalOcean's virtual machines, called Droplets.
- Implementaion of Gaussian Process Recurrent Neural Networks developed in "Neural Dynamics Discovery via Gaussian Process Recurrent Neuraβ¦β40Dec 8, 2022Updated 3 years ago
- Deep GPs built on top of TensorFlow/Keras and GPflowβ130Sep 30, 2026Updated 2 weeks ago
- Keras + Gaussian Processes: Learning scalable deep and recurrent kernels.β250Aug 2, 2024Updated 2 years ago
- code supplement for variational boosting (https://arxiv.org/abs/1611.06585)β11Jul 24, 2017Updated 9 years ago
- Python library for Recurrent Gaussian Processesβ22Oct 20, 2017Updated 8 years ago
- A bare-bones TensorFlow framework for Bayesian deep learning and Gaussian process approximationβ127Jul 27, 2021Updated 5 years ago
- Gaussian Processes in Pytorchβ76Feb 26, 2020Updated 6 years ago
- A community repository for benchmarking Bayesian methodsβ112Nov 29, 2021Updated 4 years ago
- Code for "Deep Convolutional Networks as shallow Gaussian Processes"β39Jun 21, 2019Updated 7 years ago
- Deploy on Railway without the complexity - Free Credits Offer β’ AdConnect your repo and Railway handles the rest with instant previews. Quickly provision container image services, databases, and storage volumes.
- β69May 26, 2018Updated 8 years ago
- Reducing Reparameterization Gradient Variance code.β33Jun 5, 2017Updated 9 years ago
- Bayesian Optimization using GPflowβ276Dec 2, 2020Updated 5 years ago
- A highly efficient implementation of Gaussian Processes in PyTorchβ3,926Oct 2, 2026Updated 2 weeks ago
- Code used in paper submitted to ICASSP 2019β14Nov 22, 2018Updated 7 years ago
- Asymmetric Transfer Learning with Deep Gaussian Processesβ18Jun 26, 2015Updated 11 years ago
- Implementation for Non-stationary Spectral Kernels (NIPS 2017)β20Jan 4, 2020Updated 6 years ago
- β12Jun 5, 2015Updated 11 years ago
- Code for a generative controller for the AI Gym cartpole taskβ15Feb 22, 2017Updated 9 years ago
- Deploy open-source AI quickly and easily - Special Bonus Offer β’ AdRunpod Hub is built for open source. One-click deployment and autoscaling endpoints without provisioning your own infrastructure.
- Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019β42Nov 29, 2022Updated 3 years ago
- β40Apr 29, 2019Updated 7 years ago
- Official code for "Efficient Deep Gaussian Process Models for Variable-Sized Inputs" - accepted in IJCNN2019β15Jul 17, 2019Updated 7 years ago
- Heterogeneous Multi-output Gaussian Processesβ55May 4, 2020Updated 6 years ago
- β21May 5, 2022Updated 4 years ago
- Nonparametric Differential Equation Modelingβ56Mar 5, 2024Updated 2 years ago
- Deep Kernel Learning. Gaussian Process Regression where the input is a neural network mapping of x that maximizes the marginal likelihoodβ96Nov 23, 2017Updated 8 years ago