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 ...

First, I want to express my sincere gratitude for your contribution of CardBench to the field of Cardinality Estimation—it has been incredibly helpful in my work. I'm replicating the Instance based ...

ABSTRACT: This study compares the Adomian Decomposition Method (ADM) and the Variational Iteration Method (VIM) for solving nonlinear differential equations in engineering. Differential equations are ...

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 ...

This paper introduces a novel hierarchical graph-based long short-term memory network designed for predicting the nonlinear seismic responses of building structures. We represent buildings as graphs ...

Researchers have discovered a method to harness energy from ambient heat using graphene, overturning long-established physics theories. This breakthrough holds promising commercial potential, ...

Abstract: Graph wavelet transforms allow for the effective representation of signals that are defined over irregular domains. The transform coefficients should be sparse, and encode salient features ...