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A Copula-based variational autoencoder for uncertainty quantification in inverse problems: application to damage identification in an offshore wind turbine

Fernandez-Navamuel, A.; Diaz Viera, Martin A.; Croci, M. (2026-01-01)

Structural health monitoring of floating offshore wind Turbines (FOWTs) is critical for ensuring operational safety and efficiency. However, identifying damage in components like mooring systems from limited sensor data pose...

Adaptive Multi-task Learning for Probabilistic Load Forecasting

Zaballa, O.; Álvarez, V.; Mazuelas, S. (2026-01-01)

Simultaneous load forecasting across multiple entities (e.g., regions, buildings) is crucial for the efficient, reliable, and cost-effective operation of power systems. Accurate load forecasting is a challenging problem d...

A Bayesian state-space model for tool wear estimation in drilling of Inconel 718

Ponce Vanegas, F.; Artabe, A.; Polvorosa, R.; Espina-Navarro, R.; Fernández, A.; Lopez de Lacalle, N. (2026-01-01)

We study the evolution of tool wear during drilling of plates of Inconel~718 under different cutting speeds. As observable variable we use the spindle motor current, so no additional sensor system is required for monito...

Understanding Entanglement through the Lens of Quantifiable Algebraic Structures: Application to Bird Navigation

Imtiyaz, S.; Rodrigues, S. (2026-01-01)

We propose a unified mathematical meta-framework for long-distance navigation in birds, based on a bundle-theoretic representation of multisensory integration within evolving combinatorial structures. Various information str...