2 papers
cs.LG2025
Enhancing Fractional Gradient Descent with Learned Optimizers
Jan Sobotka, Petr Šimánek, Pavel Kordík
Fractional Gradient Descent (FGD) offers a novel and promising way to accelerate optimization by incorporating fractional calculus into machine learning. Although FGD has shown enc…
cs.CV2025
Downscaling climate projections to 1 km with single-image super resolution
Petr Košťál, Pavel Kordík, Ondřej Podsztavek
High-resolution climate projections are essential for local decision-making. However, available climate projections have low spatial resolution (e.g. 12.5 km), which limits their u…