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BCAM people
José Antonio Lozano, BCAM Scientific Director and Professor of Computer Science and Artificial Intelligence at the University of the Basque Country (EHU), was awarded the prestigious 2024 Euskadi Research Award for his contributions to Science and Technology by the Lehendakari Imanol Pradales and…
BCAM people
Mikel Florez will defend his thesis on Monday, July 7th
The defence will take place at Sala Adela Room at the Faculty of Science and Technology of Leioa EHU Campus at 11:00 h
About the center
- The competition took place last weekend at the Bilbaina Society as part of Bilbomath, a collaboration between the Bilbao City Council and BCAM aimed at promoting inte
About the center
Summer School on Post-Quantum Cryptography: Bridging the Future of Cybersecurity
- An intensive course hosted by BCAM introduced students and researchers to the forefront of post-quantum cryptography — from lattice-based systems to hash-based signatures — preparing t
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View allA Unified View of Double-Weighting for Marginal Distribution Shift
Segovia, J.I; Mazuelas, S.; Liu, A. (2025-03-01)
Supervised classification traditionally assumes that training and testing samples are drawn from the same underlying distribution. However, practical scenarios are often affected by distribution shifts, such as covariate and...
Collocation-based robust variational physics-informed neural networks (CRVPINNs)
Paszyński, Maciej; Los, M.; Służalec, T.; Maczuga, P.; Vilkha, A.; Uriarte, C. (2025-09-01)
Physics-informed neural networks (PINNs) have been widely used to solve partial differential equations (PDEs) through strong residual minimization formulations. Their extension to weak scenarios via Variational PINNs (VPINNs...
Concave Grain Boundaries Stabilized by Boron Segregation for Efficient and Durable Oxygen Reduction
Geng, X.; Vega-Paredes, M.; Lu, X.; Chakraborty, P.; Li, Y.; Scheu, C.; Wang, Z.; Gault, B. (2024-09-17)
The oxygen reduction reaction (ORR) is a critical process that limits the efficiency of fuel cells and metal-air batteries due to its slow kinetics, even when catalyzed by platinum (Pt). To reduce Pt usage, enhancing both th...
Multi-task Online Learning for Probabilistic Load Forecasting
Zaballa, O.; Álvarez, V.; Mazuelas, S. (2024-11-01)
Load forecasting is essential for the efficient, reliable, and cost-effective management of power systems. Load forecasting performance can be improved by learning the similarities among multiple entities (e.g., regions, bui...