A new technical paper titled “Massively parallel and universal approximation of nonlinear functions using diffractive processors” was published by researchers at UCLA. “Nonlinear computation is ...

STG-DMD (Sparse-Coded Time-Delay Graph Dynamic Mode Decomposition) is a data-driven framework for modeling nonlinear dynamics on graph structures. It integrates: StgDmd/ ├── code/ │ ├── artificial/ │ ...

Activation functions play a critical role in AI inference, helping to ferret out nonlinear behaviors in AI models. This makes them an integral part of any neural network, but nonlinear functions can ...

In this paper, we define some non-elementary amplitude functions that are giving solutions to some second-order nonlinear ODEs with forcing term and systems of ODEs with chaotic behavior, such as the ...

Abstract: The distributed nonlinear adaptive graph filter (DNAGF) is developed with the single nonlinear graph filter model (NGFM) to handle streaming datasets. However, the current DNAGFs tend to ...

While retrieval-augmented generation is effective for simpler queries, advanced reasoning questions require deeper connections between information that exist across documents. They require a knowledge ...

Ames National Laboratory, U.S. Department of Energy, Ames, Iowa 50011, United States Department of Physics and Astronomy, Iowa State University, Ames, Iowa 50011, United States ...

Many types of economic problems require that we consider two variables at the same time. A typical example is the relation between price of a commodity and the demand or supply of that commodity. The ...

Abstract: The affinity graph is regarded as a mathematical representation of the local manifold structure. The performance of locality-preserving projections (LPPs) and its variants is tied to the ...