alan-turing-institute / mogp-emulatorLinks
Package for fitting Gaussian Process Emulators to multiple output computer simulation results.
☆53Updated 2 years ago
Alternatives and similar repositories for mogp-emulator
Users that are interested in mogp-emulator are comparing it to the libraries listed below
Sorting:
- Python package 'dgpsi' for deep and linked Gaussian process emulations☆28Updated last month
- Literature and light wrappers for gaussian process models.☆47Updated 4 years ago
- Easy emulating of geophysical models including (but not limited to!) Earth System Models.☆59Updated 10 months ago
- Lightweight library for probabilistic forecast evaluation and optimization.☆68Updated this week
- A Python toolbox for Bayesian inference and generative sampling, implementing triangular transport maps from samples.☆12Updated last week
- Python codes for studying predictability and data assimlation with a surface quasi-geostrophic turbulence model☆39Updated this week
- Collection of resources from each meetup event☆13Updated 5 years ago
- Code repository for paper: An ensemble score filter for tracking high-dimensional nonlinear dynamical systems☆20Updated last year
- WAVI ice sheet model☆32Updated last month
- ¡AnDA! is a Python library for the Analog Data Assimilation.☆28Updated 4 years ago
- ☆59Updated 2 years ago
- Jupyter notebook tutorials on various machine learning topics☆25Updated 2 weeks ago
- Official implementation of Score-based Data Assimilation☆80Updated 2 years ago
- A framework for composing Neural Processes in Python☆89Updated last year
- Flexible and efficient tools for high-dimensional approximation, scientific machine learning and uncertainty quantification.☆68Updated last week
- This repository is a resource complementary to the book: Data Assimilation Fundamental: A unified formulation for state and parameter est…☆53Updated 9 months ago
- PyDA: A hands-on introduction to dynamical data assimilation with Python☆76Updated 5 years ago
- Experiments demonstrating coupled online learning for machine learning parameterizations☆22Updated 2 years ago
- Kernel methods for statistical modeling of dynamical systems☆26Updated 3 months ago
- Uncertainty quantification for machine learning at Cooperative Institute for Research in the Atmosphere☆20Updated 3 years ago
- Model of an idealized Moist Atmosphere: Intermediate-complexity General Circulation Model with full radiation☆36Updated 2 years ago
- Lorenz 1996 two time-scale model for learning machine learning☆58Updated last month
- ☆27Updated 4 months ago
- explore the FV3 data for parameterization☆17Updated last year
- Python code for data assimilation methods☆52Updated 2 years ago
- Jatmos is a scalable simulator for atmospheric dynamics, written in JAX.☆35Updated 9 months ago
- XRO: Extended nonlinear Recharge Oscillator model☆27Updated 4 months ago
- Python code for "Applications of Deep Learning to Ocean Data Inference and Sub-Grid Parameterisation" (https://doi.org/10.1029/2018MS0014…☆49Updated 7 years ago
- Multi-Output Gaussian Process Toolkit☆183Updated 7 months ago
- Research and experiments for downscaling climate/weather data via generative learning☆38Updated 3 years ago