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: "anatomy of a bit information in a time series observation"
  Abstract: Appealing to several multivariate information measures—some familiar, some new here—we analyze the information embedded in discrete-valued stochastic time series. We dissect the uncertainty of a single observation to demonstrate how the measures’ asymptotic behavior sheds structural and semantic light on the generating process’s internal information dynamics. The measures scale with the length of time window, which captures both intensive (rates of growth) and subextensive components. We provide interpretations for the components, developing explicit relationships between them. We also identify the informational component shared between the past and the future that is not contained in a single observation. The existence of this component directly motivates the notion of a process’s effective (internal) states and indicates why one must build models.

Connected through hyperedge HE-1 (induced by source paper "quantifying high order interdependencies via multivariate extensions of the mutual information"):
  with members:
    - "pointwise partial information decomposition using the specificity and ambiguity lattices"
    - "measuring multivariate redundant information with pointwise common change in surprisal"
    - "multivariate dependence beyond shannon information"
    - "understanding interdependency through complex information sharing"
    - "exploration of synergistic and redundant information sharing in static and dynamical gaussian systems"
    - "quantifying synergistic mutual information"
    - "nonnegative decomposition of multivariate information"

Connected through hyperedge HE-2 (induced by source paper "characterizing information theoretic storage and transfer in continuous time processes"):
  with members:
    - "transfer entropy in continuous time with applications to jump and neural spiking processes"
    - "leveraging information storage to select forecast optimal parameters for delay coordinate reconstructions"

Connected through hyperedge HE-3 (induced by source paper "assessing information transmission in data transformations with the channel multivariate entropy triangle"):
  with members:
    - "multivariate dependence beyond shannon information"

Connected through hyperedge HE-4 (induced by source paper "multivariate dependence beyond shannon information"):
  with members:
    - "invariant components of synergy redundancy and unique information among three variables"
    - "measuring multivariate redundant information with pointwise common change in surprisal"
    - "understanding interdependency through complex information sharing"
    - "extropy complementary dual of entropy"
    - "model free quantification of time series predictability"
    - "quantifying unique information"
    - "intersection information based on common randomness"
    - "bivariate measure of redundant information"

Connected through hyperedge HE-5 (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"
    - "towards a synergy based approach to measuring information modification"
    - "the diminishing role of hubs in dynamical processes on complex networks"
    - "nonnegative decomposition of multivariate information"

Connected through hyperedge HE-6 (induced by source paper "understanding interdependency through complex information sharing"):
  with members:
    - "exploration of synergistic and redundant information sharing in static and dynamical gaussian systems"
    - "justification of logarithmic loss via the benefit of side information"
    - "quantifying unique 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-7 (induced by source paper "specific differential entropy rate estimation for continuous valued time series"):
  with members:
    - "a non parametric k nearest neighbour entropy estimator"
    - "estimating mutual information by local gaussian approximation"

Connected through hyperedge HE-8 (induced by source paper "sequential complexity as a descriptor for musical similarity"):
  with members:
    - "identifying cover songs using information theoretic measures of similarity"
    - "on prediction using variable order markov models"

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)