Light-weighted code for Orthogonal Additive Gaussian Processes
☆46Jul 30, 2024Updated 2 years ago
Alternatives and similar repositories for orthogonal-additive-gaussian-processes
Users that are interested in orthogonal-additive-gaussian-processes 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 with Importance-Weighted Variational Inference☆37May 30, 2019Updated 7 years ago
- A library implementing the kernels for and experiments using extrinsic gauge equivariant vector field Gaussian Processes☆26Oct 28, 2021Updated 4 years ago
- Gaussian processes regression models with linear inequality constraints☆16Jul 10, 2024Updated 2 years ago
- Code for 'Memory-based dual Gaussian processes for sequential learning' (ICML 2023)☆12Aug 16, 2023Updated 3 years ago
- Deep GPs built on top of TensorFlow/Keras and GPflow☆130Sep 30, 2026Updated 3 weeks ago
- Managed Kubernetes at scale on DigitalOcean • AdDigitalOcean Kubernetes includes the control plane, bandwidth allowance, container registry, automatic updates, and more for free.
- Code related to the paper "Asynchronous Batch Bayesian Optimisation with Improved Local Penalisation"☆13May 8, 2019Updated 7 years ago
- Computational statistics and machine learning reading group at Imperial College London (2019-2020)☆27Aug 23, 2026Updated 2 months ago
- Convolutional Gaussian processes based on GPflow.☆95Oct 31, 2017Updated 8 years ago
- Source for experiments in the Additive Gaussian process paper, as well as extensions relating to dropout.☆21Mar 10, 2014Updated 12 years ago
- Bayesian Committee Machines in Python with GPy and multiprocessing☆20Feb 16, 2019Updated 7 years ago
- Evaluating variational inference using Pareto-smoothed importance sampling and simulation-based calibration☆12Jun 8, 2018Updated 8 years ago
- A community repository for benchmarking Bayesian methods☆112Nov 29, 2021Updated 4 years ago
- NUBO is a Bayesian optimisation framework for the optimisation of expensive-to-evaluate black-box functions developed by the Fluid Dynami…☆15Sep 11, 2025Updated last year
- ☆25Sep 10, 2023Updated 3 years ago
- Managed Kubernetes at scale on DigitalOcean • AdDigitalOcean Kubernetes includes the control plane, bandwidth allowance, container registry, automatic updates, and more for free.
- Python model for constrained GP☆28Apr 14, 2021Updated 5 years ago
- UAI paper 'Expressive Priors in Bayesian Neural Networks: Kernel Combinations and Periodic Functions'☆11Jun 26, 2019Updated 7 years ago
- A lightweight didactic library of kernel methods using the back-end JAX.☆12Mar 8, 2023Updated 3 years ago
- A Julia implementation of sparse Gaussian processes via path-wise doubly stochastic variational inference.☆33Aug 27, 2020Updated 6 years ago
- Kernel Identification Through Transformers☆14May 19, 2023Updated 3 years ago
- PyTorch implementation of the Covariate-GPLVM☆26Mar 1, 2020Updated 6 years ago
- Supplementary code for the NeurIPS 2020 paper "Matern Gaussian processes on Riemannian manifolds".☆31Feb 3, 2025Updated last year
- A Bayesian optimization toolbox built on TensorFlow☆254Oct 15, 2026Updated last week
- Code for efficiently sampling functions from GP(flow) posteriors☆76Nov 13, 2020Updated 5 years ago
- Deploy on Railway without the complexity - Free Credits Offer • AdConnect your repo and Railway handles the rest with instant previews. Quickly provision container image services, databases, and storage volumes.
- A Tensorflow based library for Time Series Modelling with Gaussian Processes☆32Apr 22, 2026Updated 6 months ago
- Reproducible code for paper "qEUBO A Decision-Theoretic Acquisition Function for Preferential Bayesian Optimization" from AISTATS 2023☆23Mar 24, 2023Updated 3 years ago
- Deep network to separate astrophysical foregrounds from cosmological signal for upcoming 21 cm radio observations. Full paper on arXiv he…☆11Jan 31, 2022Updated 4 years ago
- ☆10Sep 23, 2019Updated 7 years ago
- A repository with implementations of major papers on Gaussian Process regression models, implemented from scratch in Python, notably incl…☆14Nov 19, 2022Updated 3 years ago
- Official code for "Efficient Deep Gaussian Process Models for Variable-Sized Inputs" - accepted in IJCNN2019☆15Jul 17, 2019Updated 7 years ago
- Gaussian process regression + automatical model selection for logitudinal -omics data☆20Mar 11, 2021Updated 5 years ago
- A Python implementation of a sum-product network with gaussian processes leafs model (SPNGP, arXiv:1809.04400)☆19Jun 29, 2023Updated 3 years ago
- code for BINOCULARS and Multi-Step BO☆12Dec 7, 2020Updated 5 years ago
- Deploy open-source AI quickly and easily - Special Bonus Offer • AdRunpod Hub is built for open source. One-click deployment and autoscaling endpoints without provisioning your own infrastructure.
- Bayes-Newton—A Gaussian process library in JAX, with a unifying view of approximate Bayesian inference as variants of Newton's method.☆243Dec 22, 2023Updated 2 years ago
- Zheng Zhao's doctoral dissertation from Aalto University☆35Oct 10, 2022Updated 4 years ago
- Implementation of GPLVM and Bayesian GPLVM in pytorch/gpytorch☆15Jun 21, 2021Updated 5 years ago
- This code package is for the Tensor-Maximum-Entropy (TME) method. This method generates random surrogate data that preserves a specified …☆18Sep 9, 2017Updated 9 years ago
- ☆13Jul 17, 2023Updated 3 years ago
- ☆10Nov 17, 2020Updated 5 years ago
- State-space deep Gaussian processes in Python and Matlab☆31Jun 12, 2022Updated 4 years ago