id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-011400-zyjd9rmp	Peixoto, Tiago P.	Network Reconstruction and Community Detection from Dynamics	2019-09-18		.txt	text/plain	3327	191	50	Researchers have approached this reconstruction task from a variety of angles, resulting in many different methods, including thresholding the correlation between time series [6] , inversion of deterministic dynamics [7] [8] [9] , statistical inference of graphical models [10] [11] [12] [13] [14] and of models of epidemic spreading [15] [16] [17] [18] [19] [20] , as well as approaches that avoid explicit modeling, such as those based on transfer entropy [21] , Granger causality [22] , compressed sensing [23] [24] [25] , generalized linearization [26] , and matching of pairwise correlations [27, 28] . [32] proposed a method to infer community structure from time-series data that bypasses network reconstruction by employing a direct modeling of the dynamics given the group assignments, instead. We take two empirical networks, the with E ¼ 39430 edges, and a food web from Little Rock Lake [46] , containing N ¼ 183 nodes and E ¼ 2434 edges, and we sample from the SIS (mimicking the spread of a pandemic) and Ising model (representing simplified interspecies interactions) on them, respectively, and evaluate the reconstruction obtained via the joint and separate inference with community detection, with results shown in Fig. 2 .	./cache/cord-011400-zyjd9rmp.txt	./txt/cord-011400-zyjd9rmp.txt