mingdeyu / DGPLinks
Python package 'dgpsi' for deep and linked Gaussian process emulations
☆27Updated this week
Alternatives and similar repositories for DGP
Users that are interested in DGP are comparing it to the libraries listed below
Sorting:
- Package for fitting Gaussian Process Emulators to multiple output computer simulation results.☆52Updated last year
- ☆38Updated 4 years ago
- Literature and light wrappers for gaussian process models.☆48Updated 4 years ago
- Flexible and efficient tools for high-dimensional approximation, scientific machine learning and uncertainty quantification.☆65Updated last week
- Use Deep Learning in Data Assimilation☆51Updated 8 months ago
- Experiments demonstrating coupled online learning for machine learning parameterizations☆22Updated 2 years ago
- A framework for composing Neural Processes in Python☆85Updated 9 months ago
- A Python toolbox for Bayesian inference and generative sampling, implementing triangular transport maps from samples.☆10Updated 2 months ago
- GNNs to predict wind farm-wide power, local flow variables and damage-equivalent loads.☆18Updated 3 months ago
- OceanBench - SSH edition☆21Updated last year
- Official implementation of Learning Dissipative Chaos In A Linear Way☆12Updated 8 months ago
- Code repository for paper: An ensemble score filter for tracking high-dimensional nonlinear dynamical systems☆17Updated 11 months ago
- Code for neural network parameterization project☆19Updated last year
- Official implementation of Score-based Data Assimilation☆72Updated last year
- Exploring how to to deal with uncertain inputs with gaussian process regression models.☆27Updated 4 years ago
- Easy emulating of geophysical models including (but not limited to!) Earth System Models.☆59Updated 7 months ago
- Uncertainty Quantification in the POD-NN framework☆23Updated 5 years ago
- An open large-scale dataset for training high-resolution physics emulators in hybrid multi-scale climate simulators.☆157Updated 8 months ago
- ☆35Updated 2 years ago
- PyDA: A hands-on introduction to dynamical data assimilation with Python☆73Updated 4 years ago
- Spatio-temporal forecasting of Lorenz96 with RC-ESN, RNN-LSTM and ANN☆44Updated 4 years ago
- How to predict extreme events in climate using rare event algorithms and modern tools of machine learning☆22Updated 6 months ago
- Streamlined version of the 4dvarnet algorithm: probably a good starting point to understand and applying it☆13Updated last week
- Python codes for studying predictability and data assimlation with a surface quasi-geostrophic turbulence model☆35Updated 6 months ago
- ☆17Updated 11 months ago
- Differentiable neural-network solver for data assimilation of ice shelves written in JAX☆35Updated 4 months ago
- Bayesian neural networks via MCMC: tutorial☆58Updated 11 months ago
- A benchmark dataset for Machine Learning emulation of atmospheric radiative transfer in weather and climate models (NeurIPS 2021 Datasets…☆41Updated 2 years ago
- Emulate simulations easily☆100Updated last week
- Intuitive scientific computing with dimension types for Jax, PyTorch, TensorFlow & NumPy☆92Updated last week