human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "information flow in computational systems"):
  Abstract: We develop a theoretical framework for defining and identifying flows of information in computational systems. Here, a computational system is assumed to be a directed graph, with "clocked" nodes that send transmissions to each other along the edges of the graph at discrete points in time. A few measures of information flow have been proposed previously in the literature, and measures of directed causal influence are currently being used as a heuristic proxy for information flow. However, there is as yet no rigorous treatment of the problem with formal definitions and clearly stated assumptions, and the process of defining information flow is often conflated with the problem of estimating it. In this work, we provide a new information-theoretic definition for information flow in a computational system, which we motivate using a series of examples. We then show that this definition satisfies intuitively desirable properties, including the existence of "information paths", along which information flows from the input of the computational system to its output. Finally, we describe how information flow might be estimated in a noiseless setting, and provide an algorithm to identify information paths on the time-unrolled graph of a computational system.

Includes members:
  Member "estimating mutual information for discrete continuous mixtures":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a theory of usable information under computational constraints")
  Member "bivariate measure of redundant information":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "an operational information decomposition via synergistic disclosure")
  Member "universal estimation of directed information":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "capacity of continuous channels with memory via directed information neural estimator")
  Member "directed information graphs":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "variable lag granger causality and transfer entropy for time series analysis")
  Member "nonnegative decomposition of multivariate information":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "an operational information decomposition via synergistic disclosure")

Question: Please tell me which class the source paper belongs to. The 40 classes are: cs.NA(Numerical Analysis), cs.MM(Multimedia), cs.LO(Logic in Computer Science), cs.CY(Computers and Society), cs.CR(Cryptography and Security), cs.DC(Distributed, Parallel, and Cluster Computing), cs.HC(Human-Computer Interaction), cs.CE(Computational Engineering, Finance, and Science), cs.NI(Networking and Internet Architecture), cs.CC(Computational Complexity), cs.AI(Artificial Intelligence), cs.MA(Multiagent Systems), cs.GL(General Literature), cs.NE(Neural and Evolutionary Computing), cs.SC(Symbolic Computation), cs.AR(Hardware Architecture), cs.CV(Computer Vision and Pattern Recognition), cs.GR(Graphics), cs.ET(Emerging Technologies), cs.SY(Systems and Control), cs.CG(Computational Geometry), cs.OH(Other Computer Science), cs.PL(Programming Languages), cs.SE(Software Engineering), cs.LG(Machine Learning), cs.SD(Sound), cs.SI(Social and Information Networks), cs.RO(Robotics), cs.IT(Information Theory), cs.PF(Performance), cs.CL(Computation and Language), cs.IR(Information Retrieval), cs.MS(Mathematical Software), cs.FL(Formal Languages and Automata Theory), cs.DS(Data Structures and Algorithms), cs.OS(Operating Systems), cs.GT(Computer Science and Game Theory), cs.DB(Databases), cs.DL(Digital Libraries), cs.DM(Discrete Mathematics). Directly output the class name.

gpt: cs.IT(Information Theory)