Ushnish-Sengupta / Model-EnsemblerLinks
Code and pretrained models accompanying the paper "Ensembling geophysical models using Bayesian Neural Networks"
☆11Updated 3 years ago
Alternatives and similar repositories for Model-Ensembler
Users that are interested in Model-Ensembler are comparing it to the libraries listed below
Sorting:
- Experiments demonstrating coupled online learning for machine learning parameterizations☆22Updated 2 years ago
- A project on how to incorporate physics constraints into deep learning architectures for downscaling or other super--resolution tasks.☆14Updated 2 years ago
- NinoLearn is a research framework for statistical ENSO prediction.☆10Updated 5 years ago
- A set of pre-processing codes, A deep convolutional neural net and post-processing codes for classifying turbulent climate patterns☆12Updated 6 years ago
- Multiple linear regression from Statsmodels library coupled with Xarray library☆14Updated 6 years ago
- ☆15Updated 11 years ago
- ☆14Updated 5 years ago
- Implementation of HySPLIT based trajectory modeling and analysis in python.☆7Updated 11 months ago
- Toolbox to use NNs in fortran☆12Updated last month
- Fast domain-aware neural network emulation of a planetary boundary layer parameterization in a numerical weather forecast model☆12Updated 6 years ago
- Neural network loss functions for regression and classification tasks that can say "I don't know".☆13Updated 3 years ago
- EnKF_seir☆22Updated 3 years ago
- OCNG/ATMO 677 Geophysical Data Assimilation☆13Updated 8 years ago
- El nino forecast based on a few machine learning methods☆24Updated 8 years ago
- Trajectory analysis software, that produces time height cross sections with residencte time clustered by surface type.☆10Updated 9 months ago
- How to predict extreme events in climate using rare event algorithms and modern tools of machine learning☆22Updated 3 months ago
- ☆10Updated 5 years ago
- Python package based on PyTorch and Dask for efficient and parallelized data assimilation of weather model data and observations on GPUs.☆14Updated 4 months ago
- ☆26Updated 2 years ago
- Python codes for studying predictability and data assimlation with a surface quasi-geostrophic turbulence model☆33Updated 4 months ago
- Deep learning model for predicting environmental variables on river systems☆21Updated 2 years ago
- Python code for "Applications of Deep Learning to Ocean Data Inference and Sub-Grid Parameterisation" (https://doi.org/10.1029/2018MS0014…☆48Updated 6 years ago
- Software for training, running and analyzing a Deep Learning Earth System Model (DLESyM)☆13Updated 2 weeks ago
- A 2-layer quasi-geostrophic atmospheric model in Python. Can be coupled to a simple land or shallow-water ocean component.☆39Updated last month
- Supplementary files and scripts for Nowack et al., Causal networks for climate model evaluation and constrained projections, Nature Commu…☆19Updated 3 years ago
- Here is a [quantile random forest](http://jmlr.org/papers/v7/meinshausen06a.html) implementation that utilizes the [SciKitLearn](https://…☆18Updated 6 months ago
- R&D Python package for processing ICON data with xarray☆10Updated last year
- Code for neural network parameterization project☆19Updated last year
- Code to support publication: Holbrook et al., Nature Communications, A global assessment of marine heatwaves and their drivers.☆19Updated 4 years ago
- Profile Classification Modelling (PCM) is an ocean data analysis method based on un-supervised classification of vertical profiles☆21Updated 6 years ago