Abstract: General graph neural networks (GNNs) implement convolution operations on graphs based on polynomial spectral filters. Existing filters with high-order polynomial approximations can detect ...

Abstract: We revisit the problem of constructing explicit pseudorandom generators that fool with error ϵ degree-d polynomials in n variables over the field F q, in ...

A graph provides a visual representation of the relationship between two or more variables. Identifying the function represented by a graph involves analyzing its key features, such as its shape, ...

ABSTRACT: This paper presents derivation of micro and macro conservation and balance laws and the constitutive theories for the linear elastic micromorphic theory, in which elasticity is considered ...

Understanding which function's graph is presented requires a systematic approach, combining visual analysis with fundamental knowledge of various function types and their characteristics. The process ...

Feynkit is a modern Python package for symbolic manipulation and analysis of Feynman integrals using parametric representations. It provides a clean, well-documented API for working with: Full ...