3 papers
cs.CV2026
Representation Learning via Composite Subspace Flow Matching
José Afonso, Mário Figueiredo
Distilling semantic meaning from raw image data remains a challenge in machine learning. Current self-supervised paradigms face a trade-off: joint-embedding architectures produce r…
cs.LG2026
Stochastic hierarchical data-driven optimization: application to plasma-surface kinetics
José Afonso, Vasco Guerra, Pedro Viegas
This work introduces a stochastic hierarchical optimization framework inspired by Sloppy Model theory for the efficient calibration of physical models. Central to this method is th…
cs.LG2026
Conditional Denoising Model as a Physical Surrogate Model
José Afonso, Pedro Viegas, Rodrigo Ventura +1
Surrogate modeling for complex physical systems typically faces a trade-off between data-fitting accuracy and physical consistency. Physics-consistent approaches typically treat ph…