human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "towards a synergy based approach to measuring information modification"
  Abstract: Distributed computation in artificial life and complex systems is often described in terms of component operations on information: information storage, transfer and modification. Information modification remains poorly described however, with the popularly-understood examples of glider and particle collisions in cellular automata being only quantitatively identified to date using a heuristic (separable information) rather than a proper information-theoretic measure. We outline how a recently-introduced axiomatic framework for measuring information redundancy and synergy, called partial information decomposition, can be applied to a perspective of distributed computation in order to quantify component operations on information. Using this framework, we propose a new measure of information modification that captures the intuitive understanding of information modification events as those involving interactions between two or more information sources. We also consider how the local dynamics of information modification in space and time could be measured, and suggest a new axiom that redundancy measures would need to meet in order to make such local measurements. Finally, we evaluate the potential for existing redundancy measures to meet this localizability axiom.

Connected through hyperedge HE-1 (induced by source paper "generalised measures of multivariate information content"):
  with members:
    - "a novel approach to multivariate redundancy and synergy"
    - "idtxl the information dynamics toolkit xl a python package for the efficient analysis of multivariate information dynamics in networks"
    - "quantifying high order interdependencies via multivariate extensions of the mutual information"
    - "unique information and secret key agreement"
    - "pointwise partial information decomposition using the specificity and ambiguity lattices"
    - "probability mass exclusions and the directed components of mutual information"
    - "invariant components of synergy redundancy and unique information among three variables"
    - "secret sharing and shared information"

Connected through hyperedge HE-2 (induced by source paper "information processing features can detect behavioral regimes of dynamical systems"):
  with members:
    - "quantifying synergistic information using intermediate stochastic variables"
    - "intersection information based on common randomness"
    - "quantifying redundant information in predicting a target random variable"
    - "the diminishing role of hubs in dynamical processes on complex networks"
    - "anatomy of a bit information in a time series observation"
    - "nonnegative decomposition of multivariate information"

Connected through hyperedge HE-3 (induced by source paper "quantifying synergistic information using intermediate stochastic variables"):
  with members:
    - "quantifying unique information"
    - "quantifying synergistic mutual information"
    - "intersection information based on common randomness"
    - "shared information new insights and problems in decomposing information in complex systems"
    - "nonnegative decomposition of multivariate information"

Connected through hyperedge HE-4 (induced by source paper "synergetic and redundant information flow detected by unnormalized granger causality application to resting state fmri"):
  with members:
    - "exploration of synergistic and redundant information sharing in static and dynamical gaussian systems"
    - "a graph algorithmic approach to separate direct from indirect neural interactions"
    - "entropy and its discontents a note on definitions"
    - "quantifying synergistic mutual information"
    - "bivariate measure of redundant information"
    - "nonnegative decomposition of multivariate information"

Connected through hyperedge HE-5 (induced by source paper "quantifying redundant information in predicting a target random variable"):
  with members:
    - "reconsidering unique information towards a multivariate information decomposition"
    - "quantifying unique information"
    - "exact common information"
    - "quantifying synergistic mutual information"
    - "intersection information based on common randomness"
    - "bivariate measure of redundant information"
    - "shared information new insights and problems in decomposing information in complex systems"
    - "nonnegative decomposition of multivariate information"

Connected through hyperedge HE-6 (induced by source paper "efficient transfer entropy analysis of non stationary neural time series"):
  with members:
    - "assessing coupling dynamics from an ensemble of time series"
    - "quantifying unique information"
    - "quantifying synergistic mutual information"
    - "bivariate measure of redundant information"
    - "shared information new insights and problems in decomposing information in complex systems"
    - "on directed information theory and granger causality graphs"
    - "nonnegative decomposition of multivariate information"

Connected through hyperedge HE-7 (induced by source paper "jidt an information theoretic toolkit for studying the dynamics of complex systems"):
  with members:
    - "assessing coupling dynamics from an ensemble of time series"
    - "efficient transfer entropy analysis of non stationary neural time series"
    - "on active information storage in input driven systems"
    - "shared information new insights and problems in decomposing information in complex systems"
    - "information theoretic measures of influence based on content dynamics"
    - "nonnegative decomposition of multivariate information"

Connected through hyperedge HE-8 (induced by source paper "quantifying synergistic mutual information"):
  with members:
    - "bivariate measure of redundant information"
    - "shared information new insights and problems in decomposing information in complex systems"
    - "nonnegative decomposition of multivariate information"
    - "the common information of n dependent random variables"

Question: Please tell me which class the center node 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)