output
19992025
most citedExplainable Artificial Intelligence (XAI) 2.0: A Manifesto of Open Challenges and Interdisciplinary Research Directions

544 citations

95 papers

physics.geo-ph2025

Shannon Entropy Estimator for the Characterization of Seismic-Volcanic Signals using Python

Ligdamis Gutiérrez, Pablo Rey Devesa, Jesús Ibáñez +1

Volcanic regions have shaped human settlements for millennia, placing over 500 million people worldwide within close proximity to active volcanoes. Predicting eruptions that threat…

nlin.AO2025★ 1 cited

Effect of diversity distribution symmetry on global oscillations of networks of excitable units

Stefano Scialla, Marco Patriarca, Els Heinsalu +2

We investigate the role of the degree of symmetry of the diversity distribution in shaping the collective dynamics of networks of coupled excitable units modeled by FitzHugh-Nagumo…

cs.AI2025★ 2 cited

From Privacy to Trust in the Agentic Era: A Taxonomy of Challenges in Trustworthy Federated Learning Through the Lens of Trust Report 2.0

Nuria Rodríguez-Barroso, Mario García-Márquez, M. Victoria Luzón +1

Federated Learning (FL) enables privacy-preserving collaborative learning, yet deployments increasingly show that privacy guarantees alone do not sustain trust in high-risk setting…

physics.ao-ph2025★ 20 cited

A Pareto-Based Sensitivity Analysis and Multiobjective Calibration Approach for Integrating Streamflow and Evaporation Data

Patricio Yeste, Lieke A. Melsen, Matilde García-Valdecasas Ojeda +3

Evaporation is gaining increasing attention as a calibration and evaluation variable in hydrologic studies that seek to improve the physical realism of hydrologic models and go bey…

cs.AI2025★ 5 cited

A three-Level Framework for LLM-Enhanced eXplainable AI: From technical explanations to natural language

Marilyn Bello, Rafael Bello, Maria-Matilde García +3

The growing application of artificial intelligence in sensitive domains has intensified the demand for systems that are not only accurate but also explainable and trustworthy. Alth…

physics.geo-ph2025★ 5 cited

RNN-DAS: A New Deep Learning Approach for Detection and Real-Time Monitoring of Volcano-Tectonic Events Using Distributed Acoustic Sensing

Javier Fernandez-Carabantes, Manuel Titos, Luca D'Auria +3

In this article, we present a novel Deep Learning model based on Recurrent Neural Networks (RNNs) with Long Short-Term Memory (LSTM) cells, designed as a real-time Volcano-seismic…