Recent research has employed chemical reaction networks (CRNs), which harness biochemical processes for computations that translate interactions involving biochemical species into graphical form.

Radial basis function neural networks (RBFs) are prime candidates for pattern classification and regression and have been used extensively in classical machine learning applications. However, RBFs ...

CryptoNets and subsequent work have demonstrated the capability of homomorphic encryption (HE) in the applications of private artificial intelligence (AI). In convolutional neural networks (CNNs), ...

Key developmental structures—neural groove, neural fold, cranial neuroport, caudal neuroport, and somite—are labeled to contextualize neural tube formation and associated defects. These conditions ...

They offer promising solutions for quantile-based analyses in decentralized sensor networks across diverse applications. It should be noted that quantile regression involves a non-differentiable ...