1 citations · 3 across the 6 of their papers we have counts for
6 papers
Explainable deep learning reveals the physical mechanisms behind the turbulent kinetic energy equation
Francisco Alcántara-Ávila, Andrés Cremades, Sergio Hoyas +1
In this work, we investigate the physical mechanisms governing turbulent kinetic energy transport using explainable deep learning (XDL). An XDL model based on SHapley Additive exPl…
Exploring the interplay between Planetary Boundaries and Sustainable Development Goals using Large Language Models
Lamyae Rhomrasi, Pilar Manchón, Ricardo Vinuesa +4
By analyzing 40,037 climate articles using Large Language Models (LLMs), we identified interactions between Planetary Boundaries (PBs) and Sustainable Development Goals (SDGs). An…
Evaluating Visual Mathematics in Multimodal LLMs: A Multilingual Benchmark Based on the Kangaroo Tests
Arnau Igualde Sáez, Lamyae Rhomrasi, Yusef Ahsini +5
Multimodal Large Language Models (MLLMs) promise advanced vision language capabilities, yet their effectiveness in visually presented mathematics remains underexplored. This paper…
Critical misalignments in climate pledges reveal imbalanced sustainable development pathways
Francesca Larosa, Fermin Mallor, S. Hoyas +4
We explore the integration of climate action and Sustainable Development Goals (SDGs) in nationally determined contributions (NDCs), revealing persistent synergies and trade-offs a…
Assessment of non-intrusive sensing in wall-bounded turbulence through explainable deep learning
A. Cremades, R. Freibergs, S. Hoyas +3
In this work we present a framework to explain the prediction of the velocity fluctuation at a certain wall-normal distance from wall measurements with a deep-learning model. For t…
Large language models in climate and sustainability policy: limits and opportunities
Francesca Larosa, Sergio Hoyas, H. Alberto Conejero +3
As multiple crises threaten the sustainability of our societies and pose at risk the planetary boundaries, complex challenges require timely, updated, and usable information. Natur…