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juannat7 authored Jul 11, 2023
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# Metaflux
This repository contains the code that accompanies the paper `Nathaniel, J., Liu, J. & Gentine, P. MetaFlux: Meta-learning global carbon fluxes from sparse spatiotemporal observations. Sci Data 10, 440 (2023). https://doi.org/10.1038/s41597-023-02349-y`.

The resulting dataset of global, high-resolution (0.25-degree), long-term (daily/monthly 2001-2021) gross primary production and ecosystem respiration are available in Zenodo at https://doi.org/10.5281/zenodo.7761881.

## Introduction
Meta-learning framework for climate sciences. Currently supports the following features:
- Takes as input timeseries data (eg. FLUXNET eddy covariance stations)
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3. (experimental) `01c_with_encoder_pipeline`: adding context encoder to current classic metalearning model

![Encoder workflow](https://github.com/juannat7/metaflux/blob/main/docs/encoder_workflow.png)
![Meta inference with context encoder](https://github.com/juannat7/metaflux/blob/main/docs/gpp_encoder_infer.jpeg)
![Meta inference with context encoder](https://github.com/juannat7/metaflux/blob/main/docs/gpp_encoder_infer.jpeg)

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