id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
r494vh5711q	Salvador Aguinaga	Generating Networks by Learning Hyperedge Replacement Grammars	1904		.txt	text/plain	191	9	28	Experimental results demonstrate that hyperedge replacement grammars offer a new way to learn network features that facilitate compelling graphical structure generation that advances network science in areas of modeling and network analysis. Evaluating network models on their ability to automatically learn the underlying features is integral to algorithm development in many areas of computational science.	cache/r494vh5711q.txt	txt/r494vh5711q.txt