Researchers at the University of California, Los Angeles (UCLA) have developed an optical computing framework that performs large-scale nonlinear computations using linear materials. Reported in ...

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 ...

This repo hosts the code for paper "Nonlinear Locality-Preserving Projections With Dynamic Graph Learning, in TNNLS-2025". The proposed method addresses two main limitations: first, the pre-designed ...

Abstract: This research introduces an approach to functional Magnetic Resonance Imaging (fMRI) analysis, focusing on Nonlinear Functional Connectivity (NFC). Traditional linear correlation methods in ...

Abstract: Extracting spatial–spectral joint features has become a critical approach for improving model classification performance in the field of hyperspectral image classification (HSIC). However, ...