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 "a differentiable measure of pointwise shared information"):
  Abstract: Partial information decomposition (PID) of the multivariate mutual information describes the distinct ways in which a set of source variables contains information about a target variable. The groundbreaking work of Williams and Beer has shown that this decomposition can not be determined from classic information theory without making additional assumptions, and several candidate measures have been proposed, often drawing on principles from related fields such as decision theory. None of these measures is differentiable with respect to the underlying probability mass function. We here present a novel measure that draws only on principles linking the local mutual information to exclusion of probability mass. This principle is foundational to the original definition of the mutual information by Fano. We reuse this principle to define measure of shared information that is differentiable and is well-defined for individual realizations of the random variables. We show that the measure can be interpreted as a local mutual information with the help of an auxiliary variable. We also show that it has a meaningful Moebius inversion on a redundancy lattice and obeys a target chain rule. We give an operational interpretation of the measure based on the decisions an agent should take if given only the shared information.

Includes members:
  Member "probability mass exclusions and the directed components of mutual information":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "generalised measures of multivariate information content")
  Member "measuring multivariate redundant information with pointwise common change in surprisal":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "an operational information decomposition via synergistic disclosure")
  Member "quantifying unique information":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "an operational information decomposition via synergistic disclosure")
  Member "quantifying synergistic mutual information":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "an operational information decomposition via synergistic disclosure")
  Member "bivariate measure of redundant information":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "an operational information decomposition via synergistic disclosure")
  Member "shared information new insights and problems in decomposing information in complex systems":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "a partial information decomposition based on causal tensors")
  Member "nonnegative decomposition of multivariate information":
    also connected through other hyperedges:
      - Hyperedge HE-7 (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)