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BCAM hosts successful edition of the Symposium on Geometry Processing 2025
The 2025 edition of the Symposium on Geometry Processing (SGP) took place from July 2–4 in Bizkaia Aretoa and brought together more than 100 participants from around the world to share and explore cutting-edge research in geometry processing The 2025 edition of the Symposium on Geometry Processing…
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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
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- 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
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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...