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 "a domain theory for statistical probabilistic programming"):
  Abstract: We give an adequate denotational semantics for languages with recursive higher-order types, continuous probability distributions, and soft constraints. These are expressive languages for building Bayesian models of the kinds used in computational statistics and machine learning. Among them are untyped languages, similar to Church and WebPPL, because our semantics allows recursive mixed-variance datatypes. Our semantics justifies important program equivalences including commutativity. #R##N#Our new semantic model is based on `quasi-Borel predomains'. These are a mixture of chain-complete partial orders (cpos) and quasi-Borel spaces. Quasi-Borel spaces are a recent model of probability theory that focuses on sets of admissible random elements. Probability is traditionally treated in cpo models using probabilistic powerdomains, but these are not known to be commutative on any class of cpos with higher order functions. By contrast, quasi-Borel predomains do support both a commutative probabilistic powerdomain and higher-order functions. As we show, quasi-Borel predomains form both a model of Fiore's axiomatic domain theory and a model of Kock's synthetic measure theory.

Includes members:
  Member "an application of computable distributions to the semantics of probabilistic programs":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "synthetic topology in homotopy type theory for probabilistic programming")
  Member "factorisation systems for logical relations and monadic lifting in type and effect system semantics":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "on the expressive power of user defined effects effect handlers monadic reflection delimited control")
  Member "measurable cones and stable measurable functions a model for probabilistic higher order programming":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "on the linear structure of cones")
  Member "a convenient category for higher order probability theory":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "towards verified stochastic variational inference for probabilistic programs")
  Member "denotational validation of higher order bayesian inference":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "correctness of sequential monte carlo inference for probabilistic programming languages")
  Member "semantics for probabilistic programming higher order functions continuous distributions and soft constraints":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "etalumis bringing probabilistic programming to scientific simulators at scale")
  Member "domains and random variables":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "measurable cones and stable measurable functions a model for probabilistic higher order programming")
  Member "reasoning about recursive probabilistic programs":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "tail bound analysis for probabilistic programs via central moments")

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.LO(Logic in Computer Science)