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: "a concavity property for the reciprocal of fisher information and its consequences on costa s epi"
  Abstract: We prove that the reciprocal of Fisher information of a log-concave probability density X in Rn is concave in t with respect to the addition of a Gaussian noise Zt=N(0,tIn). As a byproduct of this result we show that the third derivative of the entropy power of a log-concave probability density X in Rn is nonnegative in t with respect to the addition of a Gaussian noise Zt. For log-concave densities this improves the well-known Costa’s concavity property of the entropy power (Costa, 1985).

Connected through hyperedge HE-1 (induced by source paper "a lower bound on the differential entropy of log concave random vectors with applications"):
  with members:
    - "forward and reverse entropy power inequalities in convex geometry"
    - "wasserstein stability of the entropy power inequality for log concave densities"
    - "the shannon lower bound is asymptotically tight"
    - "links between the logarithmic sobolev inequality and the convolution inequalities for entropy and fisher information"
    - "entropy bounds on abelian groups and the ruzsa divergence"
    - "data compression with low distortion and finite blocklength"
    - "a strengthened entropy power inequality for log concave densities"
    - "the entropy per coordinate of a random vector is highly constrained under convexity conditions"

Connected through hyperedge HE-2 (induced by source paper "convexity of mutual information along the ornstein uhlenbeck flow"):
  with members:
    - "convexity of mutual information along the heat flow"
    - "information and estimation in fokker planck channels"
    - "higher order derivatives in costa s entropy power inequality"
    - "information theoretic proofs of entropy power inequalities"
    - "estimation in gaussian noise properties of the minimum mean square error"
    - "generalized entropy power inequalities and monotonicity properties of information"
    - "mutual information and minimum mean square error in gaussian channels"

Connected through hyperedge HE-3 (induced by source paper "on the entropy power inequality for the r enyi entropy of order 0 1"):
  with members:
    - "a lower bound on the differential entropy of log concave random vectors with applications"
    - "forward and reverse entropy power inequalities in convex geometry"
    - "wasserstein stability of the entropy power inequality for log concave densities"
    - "on renyi entropy power inequalities"
    - "variants of the entropy power inequality"
    - "a strengthened entropy power inequality for log concave densities"
    - "the entropy per coordinate of a random vector is highly constrained under convexity conditions"
    - "generalized entropy power inequalities and monotonicity properties of information"

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)