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cs.LG2026
Anytime PAC-Bayes for Constrained Density-Ratio Networks under Covariate Shift
Paulo Akira F. Enabe, Rodrigo Provasi
A unified framework for learning under covariate shift is presented, in which a constrained density-ratio network approximates the Radon-Nikodym derivative and fe…
cs.LG2025
A Hybrid Virtual Element Method and Deep Learning Approach for Solving One-Dimensional Euler-Bernoulli Beams
Paulo Akira F. Enabe, Rodrigo Provasi
A hybrid framework integrating the Virtual Element Method (VEM) with deep learning is presented as an initial step toward developing efficient and flexible numerical models for one…