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Master shortest path algorithms for smarter problem solving

Shortest path algorithms like Dijkstra, BFS, and advanced approximations power everything from Google Maps to network routing. Understanding when and how to apply them can save time and resources in ...
Frontiers

Inferred global dense residue transition graphs from primary structure sequences enable protein interaction prediction via directed graph convolutional neural networks

Accurate prediction of protein-protein interactions (PPIs) is crucial for understanding cellular functions and advancing the development of drugs. While existing in-silico methods leverage direct ...
Mediaite

‘Idiocracy’: Trump Aide Mocked For Sharing Graph on Far-Left Versus Far-Right Violence

White House Deputy Press Secretary Abigail Jackson sparked a bevy of mockery over the weekend when she shared a graph from Axios highlighting the increase of left-wing violence this year, but that ...
ZDNet

Graph databases are exploding, thanks to the AI boom - here's why

I wore the world's first HDR10 smart glasses TCL's new E Ink tablet beats the Remarkable and Kindle Anker's new charger is one of the most unique I've ever seen Best laptop cooling pads Best flip ...
IEEE

Prescribed-Time Nash Equilibrium Seeking for Pursuit–Evasion Game Under Intermittent Control With Undirected/Directed Graph

Abstract: This article studies the prescribed-time Nash equilibrium (PTNE) seeking problem of the pursuit–evasion game (PEG) with second-order dynamics under the intermittent control (IC) strategy. To ...
IEEE

Vertex-Frequency Analysis on Directed Graphs

Abstract: Vertex-frequency analysis (VFA) is a useful technique in graph signal processing to extract the correspondence between frequencies and vertices. VFA can be calculated by the windowed graph ...
Frontiers

Both k-core percolation and directed graph analysis revealed succession and transition of voxels’ spatiotemporal progress on dynamic correlation resting-state fMRI

Directed graphs and their afferent/efferent capacities are produced by Markov modeling of the universal cover of undirected graphs simultaneously with the calculation of volume entropy. Using these ...
marktechpost

Neural SpaceTimes (NSTs): A Class of Trainable Deep Learning-based Geometries that can Universally Represent Nodes in Weighted Directed Acyclic Graphs (DAGs) as Events in a ...

Directed graphs are crucial in modeling complex real-world systems, from gene regulatory networks and flow networks to stochastic processes and graph metanetworks. Representing these directed graphs ...
C&EN

Directed Electrostatics Strategy Integrated as a Graph Neural Network Approach for Accelerated Cluster Structure Prediction

Advanced Artificial Intelligence Theoretical and Computational Chemistry Laboratory, School of Chemistry, University of Hyderabad, Hyderabad, Telangana 500046, India ...