Implementation of the Gaussian Process Autoregressive Regression Model
☆70Jan 17, 2025Updated last year
Alternatives and similar repositories for gpar
Users that are interested in gpar are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- Applications of Gaussian Process Latent Variable Models in Finance☆11Aug 23, 2022Updated 4 years ago
- Gaussian processes with spherical harmonic features in JAX☆16Aug 24, 2025Updated last year
- multivariate Gaussian process regression and multivariate Student-t process regression☆77Dec 3, 2025Updated 10 months ago
- Code for AutoGP☆27Jul 19, 2019Updated 7 years ago
- A community repository for benchmarking Bayesian methods☆112Nov 29, 2021Updated 4 years ago
- Deploy to Railway using AI coding agents - Free Credits Offer • AdUse Claude Code, Codex, OpenCode, and more. Autonomous software development now has the infrastructure to match with Railway.
- Gaussian process modelling in Python☆226Dec 15, 2024Updated last year
- Streaming sparse Gaussian process approximations☆70Oct 5, 2022Updated 4 years ago
- Code for the paper 'Efficient Variational Inference for Gaussian Process Regression Networks'☆22Jan 2, 2014Updated 12 years ago
- Deep GPs built on top of TensorFlow/Keras and GPflow☆130Sep 30, 2026Updated 2 weeks ago
- Approximate inference for Markov Gaussian processes using iterated Kalman smoothing, in JAX☆103Jul 6, 2023Updated 3 years ago
- Gaussian Online Processes for Python☆19Jan 5, 2025Updated last year
- Gaussian process regression code.☆25Apr 24, 2014Updated 12 years ago
- Codes for Hilbert space reduced-rank GP regression☆15Jul 30, 2019Updated 7 years ago
- Probabilistic Programming with Gaussian processes in Julia☆341Apr 1, 2025Updated last year
- Wordpress hosting with auto-scaling - Free Trial Offer • AdFully Managed hosting for WordPress and WooCommerce businesses that need reliable, auto-scalable performance. Cloudways SafeUpdates now available.
- Gaussian process time-frequency analysis toy examples☆17Apr 5, 2019Updated 7 years ago
- Repository for the work Transforming Gaussian Processes with Normalizing Flows published at AISTATS 2021☆26Dec 19, 2022Updated 3 years ago
- Heteroscedastic Bayesian Optimisation in Numpy☆24Feb 15, 2023Updated 3 years ago
- Infinite-horizon Gaussian processes☆33Sep 28, 2020Updated 6 years ago
- Painless optimisation of constrained variables in AutoGrad, TensorFlow, PyTorch, and JAX☆23Mar 6, 2023Updated 3 years ago
- Bayesian Linear Regression in Julia☆30Aug 29, 2025Updated last year
- A Tensorflow based library for Time Series Modelling with Gaussian Processes☆32Apr 22, 2026Updated 5 months ago
- Stochastic variational heteroscedastic Gaussian process☆15Mar 29, 2019Updated 7 years ago
- A curated list of awesome variational inference☆28Aug 11, 2020Updated 6 years ago
- AI Agents on DigitalOcean Gradient AI Platform • AdBuild production-ready AI agents using customizable tools or access multiple LLMs through a single endpoint. Create custom knowledge bases or connect external data.
- Continual Gaussian Processes☆32Jul 6, 2023Updated 3 years ago
- Code for Tajima et al. (2019). Optimal policy for multi-alternative decisions. Nature Neuroscience.☆10Aug 23, 2019Updated 7 years ago
- Implementation of GPLVM and Bayesian GPLVM in pytorch/gpytorch☆15Jun 21, 2021Updated 5 years ago
- Implementation for Non-stationary Spectral Kernels (NIPS 2017)☆20Jan 4, 2020Updated 6 years ago
- Code for efficiently sampling functions from GP(flow) posteriors☆76Nov 13, 2020Updated 5 years ago
- Library for Deep Gaussian Processes based on GPflow☆18Mar 31, 2020Updated 6 years ago
- Scalable Gaussian Process Regression Networks☆29Dec 20, 2022Updated 3 years ago
- Gaussian Process Regression Network code☆13Sep 3, 2013Updated 13 years ago
- Sample code for the NIPS paper "Scalable Variational Inference for Dynamical Systems"☆27Mar 29, 2019Updated 7 years ago
- Serverless GPU API endpoints on Runpod - Get Bonus Credits • AdSkip the infrastructure headaches. Auto-scaling, pay-as-you-go, no-ops approach lets you focus on innovating your application.
- Fast inference for Gaussian processes in problems involving time. Partly built on results from https://proceedings.mlr.press/v161/tebbutt…☆122Mar 12, 2026Updated 7 months ago
- Official Implementation of "Doubly Mixed-Effects Gaussian Process Regression" (Jun Ho Yoon, Daniel P. Jeong, Seyoung Kim) (AISTATS 2022, …☆12Jul 13, 2022Updated 4 years ago
- Materials for the 2017 QMSS Python Workshop☆13Jun 22, 2017Updated 9 years ago
- 🤿 Implementation of doubly stochastic deep Gaussian Process using GPflow and TensorFlow 2.0☆25Feb 11, 2024Updated 2 years ago
- A framework for composing Neural Processes in Julia☆74May 3, 2021Updated 5 years ago
- A comparison of PPL APIs☆27Jul 23, 2019Updated 7 years ago
- R&D Python package for processing ICON data with xarray☆10Jul 26, 2023Updated 3 years ago