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: "network information flow with correlated sources"
  Abstract: In this paper, we consider a network communications problem in which multiple correlated sources must be delivered to a single data collector node, over a network of noisy independent point-to-point channels. We prove that perfect reconstruction of all the sources at the sink is possible if and only if, for all partitions of the network nodes into two subsets S and S^c such that the sink is always in S^c, we have that H(U_S|U_{S^c}) < \sum_{i\in S,j\in S^c} C_{ij}. Our main finding is that in this setup a general source/channel separation theorem holds, and that Shannon information behaves as a classical network flow, identical in nature to the flow of water in pipes. At first glance, it might seem surprising that separation holds in a fairly general network situation like the one we study. A closer look, however, reveals that the reason for this is that our model allows only for independent point-to-point channels between pairs of nodes, and not multiple-access and/or broadcast channels, for which separation is well known not to hold. This ``information as flow'' view provides an algorithmic interpretation for our results, among which perhaps the most important one is the optimality of implementing codes using a layered protocol stack.

Connected through hyperedge HE-1 (induced by source paper "capacity bounds for networks with correlated sources and characterisation of distributions by entropies"):
  with members:
    - "cut set bounds on network information flow"
    - "characterising probability distributions via entropies"
    - "beyond the cut set bound uncertainty computations in network coding with correlated sources"
    - "beyond the cut set bound uncertainty computations in network coding with correlated sources"
    - "network coding capacity a functional dependence bound"
    - "dualities between entropy functions and network codes"

Connected through hyperedge HE-2 (induced by source paper "cut set bounds on network information flow"):
  with members:
    - "beyond the cut set bound uncertainty computations in network coding with correlated sources"
    - "beyond the cut set bound uncertainty computations in network coding with correlated sources"
    - "network coding capacity a functional dependence bound"
    - "the minimal set of ingleton inequalities"
    - "dualities between entropy functions and network codes"

Connected through hyperedge HE-3 (induced by source paper "source and physical layer network coding for correlated two way relaying"):
  with members:
    - "compressed relaying for two way relay networks with correlated sources"
    - "a distributed differential space time coding scheme with analog network coding in two way relay networks"
    - "physical layer network coding tutorial survey and beyond"
    - "implementation of physical layer network coding"

Connected through hyperedge HE-4 (induced by source paper "self organizing networks of information gathering cognitive agents"):
  with members:
    - "social data offloading in d2d enhanced cellular networks by network formation games"
    - "conjoining speeds up information diffusion in overlaying social physical networks"
    - "dynamic network formation with incomplete information"
    - "a game theoretic analysis of incentives in content production and sharing over peer to peer networks"
    - "coalition formation games for distributed cooperation among roadside units in vehicular networks"
    - "coalitional games for distributed collaborative spectrum sensing in cognitive radio networks"
    - "minimum cost distributed source coding over a network"

Connected through hyperedge HE-5 (induced by source paper "a multiway relay channel with balanced sources"):
  with members:
    - "information theoretic caching sequential coding for computing"
    - "multi way relay networks orthogonal uplink source channel separation and code design"
    - "the three user finite field multi way relay channel with correlated sources"
    - "the capacity region of restricted multi way relay channels with deterministic uplinks"
    - "the capacity region of multiway relay channels over finite fields with full data exchange"
    - "malleable coding with fixed reuse"

Connected through hyperedge HE-6 (induced by source paper "models statistics and rates of binary correlated sources"):
  with members:
    - "orthogonality and cooperation in collaborative spectrum sensing through mimo decision fusion"
    - "code design for the noisy slepian wolf problem"

Connected through hyperedge HE-7 (induced by source paper "spatially coupled ldpc codes for decode and forward relaying of two correlated sources over the bec"):
  with members:
    - "source channel coding theorems for the multiple access relay channel"
    - "threshold saturation via spatial coupling why convolutional ldpc ensembles perform so well over the bec"
    - "universality for the noisy slepian wolf problem via spatial coupling"
    - "bilayer ldpc convolutional codes for half duplex relay channels"
    - "ldpc code design for transmission of correlated sources across noisy channels without csit"
    - "asymptotically regular ldpc codes with linear distance growth and thresholds close to capacity"
    - "can iterative decoding for erasure correlated sources be universal"
    - "bilayer low density parity check codes for decode and forward in relay channels"

Connected through hyperedge HE-8 (induced by source paper "beyond the cut set bound uncertainty computations in network coding with correlated sources"):
  with members:
    - "on secure network coding with uniform wiretap sets"
    - "beyond the cut set bound uncertainty computations in network coding with correlated sources"
    - "multishot codes for network coding using rank metric codes"
    - "network coding capacity a functional dependence bound"
    - "packing and covering properties of subspace codes for error control in random linear network coding"
    - "a rank metric approach to error control in random network coding"
    - "coding for errors and erasures in random network coding"
    - "packing and covering properties of rank metric codes"

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)