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: "links between the logarithmic sobolev inequality and the convolution inequalities for entropy and fisher information"
  Abstract: Relative to the Gaussian measure on $\mathbb{R}^d$, entropy and Fisher information are famously related via Gross' logarithmic Sobolev inequality (LSI). These same functionals also separately satisfy convolution inequalities, as proved by Stam. We establish a dimension-free inequality that interpolates among these relations. Several interesting corollaries follow: (i) the deficit in the LSI satisfies a convolution inequality itself; (ii) the deficit in the LSI controls convergence in the entropic and Fisher information central limit theorems; and (iii) the LSI is stable with respect to HWI jumps (i.e., a jump in any of the convolution inequalities associated to the HWI functionals). #R##N#Another consequence is that the convolution inequalities for Fisher information and entropy powers are reversible in general, up to a factor depending on the Stam defect. An improved form of Nelson's hypercontractivity estimate also follows. Finally, we speculate on the possibility of an analogous reverse Brunn-Minkowski inequality and a related upper bound on surface area associated to Minkowski sums.

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"
    - "a concavity property for the reciprocal of fisher information and its consequences on costa s epi"
    - "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 "optimal transportation to the entropy power inequality"):
  with members:
    - "at every corner determining corner points of two user gaussian interference channels"
    - "yet another proof of the entropy power inequality"
    - "wasserstein continuity of entropy and outer bounds for interference channels"
    - "beyond the entropy power inequality via rearrangements"
    - "information theoretic proofs of entropy power inequalities"
    - "a simple proof of the entropy power inequality via properties of mutual information"
    - "generalized entropy power inequalities and monotonicity properties of information"

Connected through hyperedge HE-3 (induced by source paper "information measures inequalities and performance bounds for parameter estimation in impulsive noise environments"):
  with members:
    - "strengthening the entropy power inequality"
    - "on properties of the support of capacity achieving distributions for additive noise channel models with input cost constraints"
    - "stable distributions as noise models for molecular communication"
    - "sumset and inverse sumset inequalities for differential entropy and mutual information"
    - "a de bruijn identity for symmetric stable laws"
    - "information theoretic proofs of entropy power inequalities"

Connected through hyperedge HE-4 (induced by source paper "wasserstein stability of the entropy power inequality for log concave densities"):
  with members:
    - "strengthening the entropy power inequality"
    - "entropy jumps for radially symmetric random vectors"
    - "yet another proof of the entropy power inequality"
    - "a strengthened entropy power inequality for log concave densities"

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)