activity
20222025
most citedEarth System Data Cubes: Avenues for advancing Earth system research

28 citations · 59 across the 7 of their papers we have counts for

collaborators

7 papers

cs.LG2025

Transformers vs. Recurrent Models for Estimating Forest Gross Primary Production

David Montero, Miguel D. Mahecha, Francesco Martinuzzi +6

Monitoring the spatiotemporal dynamics of forest CO uptake (Gross Primary Production, GPP), remains a central challenge in terrestrial ecosystem research. While Eddy Covariance…

cs.LG2025

Unified Implementations of Recurrent Neural Networks in Multiple Deep Learning Frameworks

Francesco Martinuzzi

Recurrent neural networks (RNNs) are a cornerstone of sequence modeling across various scientific and industrial applications. Owing to their versatility, numerous RNN variants hav…

cs.CV2024★ 28 cited

Earth System Data Cubes: Avenues for advancing Earth system research

David Montero, Guido Kraemer, Anca Anghelea +15

Recent advancements in Earth system science have been marked by the exponential increase in the availability of diverse, multivariate datasets characterised by moderate to high spa…

cs.AI2024★ 3 cited

AI for Extreme Event Modeling and Understanding: Methodologies and Challenges

Gustau Camps-Valls, Miguel-Ángel Fernández-Torres, Kai-Hendrik Cohrs +22

In recent years, artificial intelligence (AI) has deeply impacted various fields, including Earth system sciences. Here, AI improved weather forecasting, model emulation, parameter…

cs.LG2024★ 2 cited

DeepExtremeCubes: Integrating Earth system spatio-temporal data for impact assessment of climate extremes

Chaonan Ji, Tonio Fincke, Vitus Benson +12

With climate extremes' rising frequency and intensity, robust analytical tools are crucial to predict their impacts on terrestrial ecosystems. Machine learning techniques show prom…

cs.LG2024★ 10 cited

Recurrent Neural Networks for Modelling Gross Primary Production

David Montero, Miguel D. Mahecha, Francesco Martinuzzi +6

Accurate quantification of Gross Primary Production (GPP) is crucial for understanding terrestrial carbon dynamics. It represents the largest atmosphere-to-land CO flux, especi…

cs.CE2022★ 16 cited

ReservoirComputing.jl: An Efficient and Modular Library for Reservoir Computing Models

Francesco Martinuzzi, Chris Rackauckas, Anas Abdelrehim +2

We introduce ReservoirComputing.jl, an open source Julia library for reservoir computing models. The software offers a great number of algorithms presented in the literature, and a…