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/ │ ...

Abstract: Graph matching is a critical task with diverse real-world applications. Current cutting-edge methodologies incorporate GNN (Graph Neural Network) combined with incremental anchor refinement, ...

Beth Skwarecki is Lifehacker’s Senior Health Editor, and holds certifications as a personal trainer and weightlifting coach. She has been writing about health for over 10 years. Add as a preferred ...

In healthcare, time series data is extensively used to track patient metrics like vital signs, lab results, and treatment responses over time. This data is critical in monitoring disease progression, ...

ABSTRACT: The exponential Randić index has important applications in the fields of biology and chemistry. The exponential Randić index of a graph G is defined as the sum of the weights e 1 d( u )d( v ...

Neural networks have been widely used to solve partial differential equations (PDEs) in different fields, such as biology, physics, and materials science. Although current research focuses on PDEs ...

Abstract: Classical graph matching aims to find a node correspondence between two unlabeled graphs of known topologies. This problem has a wide range of applications, from matching identities in ...

If your kid thinks math is “boring” (or if they break into a full meltdown at the mention of the word), I’ve got a secret weapon: Coordinate Graphing Picture Worksheets. Yep—math in disguise. These ...

When learning algebra, one of the most crucial skills to acquire is understanding how to graph linear equations. It helps you visualize relationships between variables and solve mathematical problems.

ABSTRACT: Two nonisomorphic graphs G and H are said to be matching equivalent if and only if G and H have the same matching polynomials. In this paper, some families matching equivalent graphs are ...