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 "jidt an information theoretic toolkit for studying the dynamics of complex systems"):
  Abstract: Complex systems are increasingly being viewed as distributed information processing systems, particularly in the domains of computational neuroscience, bioinformatics and Artificial Life. This trend has resulted in a strong uptake in the use of (Shannon) information-theoretic measures to analyse the dynamics of complex systems in these fields. We introduce the Java Information Dynamics Toolkit (JIDT): a Google code project which provides a standalone, (GNU GPL v3 licensed) open-source code implementation for empirical estimation of information-theoretic measures from time-series data. While the toolkit provides classic information-theoretic measures (e.g. entropy, mutual information, conditional mutual information), it ultimately focusses on implementing higher-level measures for information dynamics. That is, JIDT focusses on quantifying information storage, transfer and modification, and the dynamics of these operations in space and time. For this purpose, it includes implementations of the transfer entropy and active information storage, their multivariate extensions and local or pointwise variants. JIDT provides implementations for both discrete and continuous-valued data for each measure, including various types of estimator for continuous data (e.g. Gaussian, box-kernel and Kraskov-Stoegbauer-Grassberger) which can be swapped at run-time due to Java's object-oriented polymorphism. Furthermore, while written in Java, the toolkit can be used directly in MATLAB, GNU Octave, Python and other environments. We present the principles behind the code design, and provide several examples to guide users.

Includes members:
  Member "assessing coupling dynamics from an ensemble of time series":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "information theory for non stationary processes with stationary increments")
  Member "efficient transfer entropy analysis of non stationary neural time series":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a graph algorithmic approach to separate direct from indirect neural interactions")
  Member "towards a synergy based approach to measuring information modification":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "generalised measures of multivariate information content")
  Member "on active information storage in input driven systems":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "guided self organization of input driven recurrent neural networks")
  Member "shared information new insights and problems in decomposing information in complex systems":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "a differentiable measure of pointwise shared information")
  Member "information theoretic measures of influence based on content dynamics":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "deep collaborative embedding for information cascade prediction")
  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)