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 "entropy jumps for radially symmetric random vectors"):
  Abstract: We establish a quantitative bound on the entropy jump associated to the sum of independent, identically distributed (IID) radially symmetric random vectors having dimension greater than one. Following the usual approach, we first consider the analogous problem of Fisher information dissipation, and then integrate along the Ornstein-Uhlenbeck semigroup to obtain an entropic inequality. In a departure from previous work, we appeal to a result by Desvillettes and Villani on entropy production associated to the Landau equation. This obviates strong regularity assumptions, such as presence of a spectral gap and log-concavity of densities, but comes at the expense of radial symmetry. As an application, we give a quantitative estimate of the deficit in the Gaussian logarithmic Sobolev inequality for radially symmetric functions.

Includes members:
  Member "strengthening the entropy power inequality":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "an entropy inequality for symmetric random variables")
  Member "wasserstein continuity of entropy and outer bounds for interference channels":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a lower bound on the expected distortion of joint source channel coding")
  Member "beyond the entropy power inequality via rearrangements":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "two remarks on generalized entropy power inequalities")
  Member "a strengthened entropy power inequality for log concave densities":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "a lower bound on the differential entropy of log concave random vectors with applications")

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)