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Abstract: Signal processing on directed acyclic graphs (DAGs) presents unique challenges. Unlike for undirected graphs, the Laplacian matrix of a DAG lacks a complete eigenbasis in general, and the ...
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 ...
Graph theory is an integral component of algorithm design that underlies sparse matrices, relational databases, and networks. Improving the performance of graph algorithms has direct implications to ...
Previous research on reasoning frameworks in large language models (LLMs) has explored various approaches to enhance problem-solving capabilities. Chain-of-Thought (CoT) introduced articulated ...