approximation theory 1dimension-independent analysis 1fractional pdes 1neural network approximation 1spectral barron spaces 1
From the 1 of 3 linked papers with an AI index.
3 papers
math.AP2026
Neural Network Approximation of Solutions to Fractional Parabolic Partial Differential Equations
Jae-Hwan Choi, Hyojae Lim, Jinsol Seo +2
The paper develops a dimension‑efficient neural network approximation theory for solutions of fractional parabolic PDEs, introducing anisotropic spectral Barron spaces and proving…
cs.LG2026
Extreme Weather Nowcasting via Local Precipitation Pattern Prediction
Changhoon Song, Teng Yuan Chang, Youngjoon Hong
Accurate forecasting of extreme weather events such as heavy rainfall or storms is critical for risk management and disaster mitigation. Although high-resolution radar observations…
cs.LG2026
Sobolev Approximation of Deep ReLU Networks in Log-Barron Space
Changhoon Song, Seungchan Ko, Youngjoon Hong
Universal approximation theorems show that neural networks can approximate any continuous function; however, the number of parameters may grow exponentially with the ambient dimens…