CarbonBench: A Global Benchmark for Upscaling of Carbon Fluxes Using Zero-Shot Learning | ScienceToStartup | ScienceToStartup

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References (39)

[1]

Task Aware Modulation Using Representation Learning for Upsaling of Terrestrial Carbon Fluxes

2026A. Rozanov, Arvind Renganathan et al.

[2]

The JapanFlux2024 dataset for eddy covariance observations covering Japan and East Asia from 1990 to 2023

2025M. Ueyama, Yuta Takao et al.

[3]

Global carbon flux dataset generated by fusing remote sensing and multiple flux networks observation

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"CarbonBench is a benchmark for evaluating zero-shot learning models in carbon flux upscaling across diverse ecosystems."

Climate Modeling•Score: 4•View PDF ↗

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CarbonBench: A Global Benchmark for Upscaling of Carbon Fluxes Using Zero-Shot Learning

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References (39)

Founder's Pitch

"CarbonBench is a benchmark for evaluating zero-shot learning models in carbon flux upscaling across diverse ecosystems."

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CarbonBench: A Global Benchmark for Upscaling of Carbon Fluxes Using Zero-Shot Learning

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References (39)

Founder's Pitch

"CarbonBench is a benchmark for evaluating zero-shot learning models in carbon flux upscaling across diverse ecosystems."

Commercial Viability Breakdown

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