Search Results - "Martinuzzi, Francesco"

A standardized catalogue of spectral indices to advance the use of remote sensing in Earth system research by Montero, David, Aybar, César, Mahecha, Miguel D., Martinuzzi, Francesco, Söchting, Maximilian, Wieneke, Sebastian

“…Spectral Indices derived from multispectral remote sensing products are extensively used to monitor Earth system dynamics (e.g. vegetation dynamics, water…”
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A sensitivity analysis of cellular automata and heterogeneous topology networks: partially-local cellular automata and homogeneous homogeneous random boolean networks by Glover, Tom Eivind, Jahren, Ruben, Martinuzzi, Francesco, Gonçalves Lind, Pedro, Nichele, Stefano

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Learning extreme vegetation response to climate drivers with recurrent neural networks by Martinuzzi, Francesco, Mahecha, Miguel D, Camps-Valls, Gustau, Montero, David, Williams, Tristan, Mora, Karin

“…The spectral signatures of vegetation are indicative of ecosystem states and health. Spectral indices used to monitor vegetation are characterized by long-term…”
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SpectralIndices.jl: Streamlining spectral indices access and computation for Earth system research by Martinuzzi, Francesco, Mahecha, Miguel D., Montero, David, Alonso, Lazaro, Mora, Karin

“…Remote sensing is an essential technology in environmental science to study Earth surface processes. In optical remote sensing, spectral indices (SI) are…”
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A Sensitivity Analysis of Cellular Automata and Heterogeneous Topology Networks: Partially-Local Cellular Automata and Homogeneous Homogeneous Random Boolean Networks by Glover, Tom Eivind, Jahren, Ruben, Martinuzzi, Francesco, Lind, Pedro Gonçalves, Nichele, Stefano

“…Elementary Cellular Automata (ECA) are a well-studied computational universe that is, despite its simple configurations, capable of impressive computational…”
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Recurrent Neural Networks for Modelling Gross Primary Production by Montero, David, Mahecha, Miguel D., Martinuzzi, Francesco, Aybar, Cesar, Klosterhalfen, Anne, Knohl, Alexander, Koebsch, Franziska, Anaya, Jesus, Wieneke, Sebastian

“…Accurate quantification of Gross Primary Production (GPP) is crucial for understanding terrestrial carbon dynamics. It represents the largest…”
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Recurrent Neural Networks for Modelling Gross Primary Production by Montero, David, Mahecha, Miguel D, Martinuzzi, Francesco, Aybar, César, Klosterhalfen, Anne, Knohl, Alexander, Koebsch, Franziska, Anaya, Jesús, Wieneke, Sebastian

“…Accurate quantification of Gross Primary Production (GPP) is crucial for understanding terrestrial carbon dynamics. It represents the largest…”
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ReservoirComputing.jl: An Efficient and Modular Library for Reservoir Computing Models by Martinuzzi, Francesco, Rackauckas, Chris, Abdelrehim, Anas, Mahecha, Miguel D, Mora, Karin

“…Journal of Machine Learning Research 23 (2022) 1-8 We introduce ReservoirComputing.jl, an open source Julia library for reservoir computing models. The…”
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Earth System Data Cubes: Avenues for advancing Earth system research by Montero, David, Kraemer, Guido, Anghelea, Anca, Aybar, César, Brandt, Gunnar, Camps-Valls, Gustau, Cremer, Felix, Flik, Ida, Gans, Fabian, Habershon, Sarah, Ji, Chaonan, Kattenborn, Teja, Martínez-Ferrer, Laura, Martinuzzi, Francesco, Reinhardt, Martin, Söchting, Maximilian, Teber, Khalil, Mahecha, Miguel D

“…Recent advancements in Earth system science have been marked by the exponential increase in the availability of diverse, multivariate datasets characterised by…”
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DeepExtremeCubes: Integrating Earth system spatio-temporal data for impact assessment of climate extremes by Ji, Chaonan, Fincke, Tonio, Benson, Vitus, Camps-Valls, Gustau, Fernandez-Torres, Miguel-Angel, Gans, Fabian, Kraemer, Guido, Martinuzzi, Francesco, Montero, David, Mora, Karin, Pellicer-Valero, Oscar J, Robin, Claire, Soechting, Maximilian, Weynants, Melanie, Mahecha, Miguel D

“…With climate extremes' rising frequency and intensity, robust analytical tools are crucial to predict their impacts on terrestrial ecosystems. Machine learning…”
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AI for Extreme Event Modeling and Understanding: Methodologies and Challenges by Camps-Valls, Gustau, Fernández-Torres, Miguel-Ángel, Cohrs, Kai-Hendrik, Höhl, Adrian, Castelletti, Andrea, Pacal, Aytac, Robin, Claire, Martinuzzi, Francesco, Papoutsis, Ioannis, Prapas, Ioannis, Pérez-Aracil, Jorge, Weigel, Katja, Gonzalez-Calabuig, Maria, Reichstein, Markus, Rabel, Martin, Giuliani, Matteo, Mahecha, Miguel, Popescu, Oana-Iuliana, Pellicer-Valero, Oscar J, Ouala, Said, Salcedo-Sanz, Sancho, Sippel, Sebastian, Kondylatos, Spyros, Happé, Tamara, Williams, Tristan

“…In recent years, artificial intelligence (AI) has deeply impacted various fields, including Earth system sciences. Here, AI improved weather forecasting, model…”
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Composing Modeling And Simulation With Machine Learning In Julia by Rackauckas, Chris, Gwozdz, Maja, Jain, Anand, Ma, Yingbo, Martinuzzi, Francesco, Rajput, Utkarsh, Saba, Elliot, Shah, Viral B., Anantharaman, Ranjan, Edelman, Alan, Gowda, Shashi, Pal, Avik, Laughman, Chris

“…In this paper we introduce JuliaSim, a high-performance programming environment designed to blend traditional modeling and simulation with machine learning…”
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Composing Modeling and Simulation with Machine Learning in Julia by Rackauckas, Chris, Anantharaman, Ranjan, Edelman, Alan, Gowda, Shashi, Gwozdz, Maja, Jain, Anand, Laughman, Chris, Ma, Yingbo, Martinuzzi, Francesco, Pal, Avik, Rajput, Utkarsh, Saba, Elliot, Shah, Viral B

“…In this paper we introduce JuliaSim, a high-performance programming environment designed to blend traditional modeling and simulation with machine learning…”
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