Müntz-Szász Networks: Neural Architectures with Learnable Power-Law Bases
Analysis
This article introduces a novel neural architecture, Müntz-Szász Networks, which utilizes learnable power-law bases. This is a research paper, likely detailing a new approach to neural network design, potentially offering improvements in areas like function approximation or data representation. The focus is on the mathematical foundations and the potential benefits of this new architecture.
Key Takeaways
Reference
“”