arxiv
PublishedSeptember 15, 2026 at 4:00 AM
Neural Operators for Nonlinear Functionals on RKHS
Publisher summary· verbatim
arXiv:2403.12187v2 Announce Type: replace-cross Abstract: Motivated by the abundance of functional data, such as time series and images, we study the approximation and statistical learning of nonlinear functionals defined on reproducing kernel Hilbert spaces (RKHSs) using neural networks. By leverag
Stay posted· Newsletter
A 5-min weekly brief — top movers, price watch, story of the week.
Discussion
No replies yet. Be first.
Related coverage
More from ARXIV
arxivSyn2Logic: End-to-End Neuromorphic Design Automation4harxivMulti-source conformal prediction: leveraging heterogeneity via localization4harxivToward a Layer-2 Trigger for AI/ML Lifecycle Management in 6G4harxivHow User-AI Mistreatment Occurs and Matters in Conversational Systems?4hThe Bubble Brief
WEEKLYRead AI insights every Tuesday — top movers, new releases, story of the week.
Originally published on arxiv ↗