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: "measurable cones and stable measurable functions a model for probabilistic higher order programming"
  Abstract: We define a notion of stable and measurable map between cones endowed with measurability tests and show that it forms a cpo-enriched cartesian closed category. This category gives a denotational model of an extension of PCF supporting the main primitives of probabilistic functional programming, like continuous and discrete probabilistic distributions, sampling, conditioning and full recursion. We prove the soundness and adequacy of this model with respect to a call-by-name operational semantics and give some examples of its denotations.

Connected through hyperedge HE-1 (induced by source paper "on the linear structure of cones"):
  with members:
    - "semantics of higher order probabilistic programs with conditioning"
    - "differentials and distances in probabilistic coherence spaces"
    - "linear logic in normed cones probabilistic coherence spaces and beyond"
    - "a domain theory for statistical probabilistic programming"
    - "mixed powerdomains for probability and nondeterminism"
    - "probabilistic call by push value"
    - "full abstraction for probabilistic pcf"

Connected through hyperedge HE-2 (induced by source paper "formal verification of higher order probabilistic programs reasoning about approximation convergence bayesian inference and optimization"):
  with members:
    - "equivalence between wasserstein and value aware model based reinforcement learning"
    - "relational reasoning for markov chains in a probabilistic guarded lambda calculus"
    - "mixed powerdomains for probability and nondeterminism"
    - "a convenient category for higher order probability theory"
    - "denotational validation of higher order bayesian inference"
    - "a theory of slicing for probabilistic control flow graphs"
    - "a relational logic for higher order programs"
    - "a program logic for union bounds"

Connected through hyperedge HE-3 (induced by source paper "a probabilistic separation logic"):
  with members:
    - "quantitative separation logic a logic for reasoning about probabilistic pointer programs"
    - "more is less perfectly secure oblivious algorithms in the multi server setting"
    - "an assertion based program logic for probabilistic programs"
    - "a separation logic for concurrent randomized programs"
    - "the beta bernoulli process and algebraic effects"
    - "a domain theory for statistical probabilistic programming"
    - "proving uniformity and independence by self composition and coupling"
    - "a language for probabilistically oblivious computation"

Connected through hyperedge HE-4 (induced by source paper "the geometry of bayesian programming"):
  with members:
    - "formal verification of higher order probabilistic programs reasoning about approximation convergence bayesian inference and optimization"
    - "a domain theory for statistical probabilistic programming"
    - "a convenient category for higher order probability theory"
    - "the geometry of parallelism classical probabilistic and quantum effects"
    - "a lambda calculus foundation for universal probabilistic programming"
    - "full abstraction for probabilistic pcf"
    - "church a language for generative models"

Connected through hyperedge HE-5 (induced by source paper "semantics of higher order probabilistic programs with conditioning"):
  with members:
    - "borel kernels and their approximation categorically"
    - "a domain theory for statistical probabilistic programming"
    - "a convenient category for higher order probability theory"
    - "denotational validation of higher order bayesian inference"
    - "semantics for probabilistic programming higher order functions continuous distributions and soft constraints"
    - "a lambda calculus foundation for universal probabilistic programming"

Connected through hyperedge HE-6 (induced by source paper "a domain theory for statistical probabilistic programming"):
  with members:
    - "an application of computable distributions to the semantics of probabilistic programs"
    - "factorisation systems for logical relations and monadic lifting in type and effect system semantics"
    - "a convenient category for higher order probability theory"
    - "denotational validation of higher order bayesian inference"
    - "semantics for probabilistic programming higher order functions continuous distributions and soft constraints"
    - "domains and random variables"
    - "reasoning about recursive probabilistic programs"
    - "a lambda calculus foundation for universal probabilistic programming"

Connected through hyperedge HE-7 (induced by source paper "an application of computable distributions to the semantics of probabilistic programs"):
  with members:
    - "a domain theory for statistical probabilistic programming"
    - "a convenient category for higher order probability theory"
    - "measure transformer semantics for bayesian machine learning"
    - "church a language for generative models"
    - "probabilistic operational semantics for the lambda calculus"
    - "computability of probability measures and martin lof randomness over metric spaces"

Connected through hyperedge HE-8 (induced by source paper "probabilistic stable functions on discrete cones are power series long version"):
  with members:
    - "semantics for probabilistic programming higher order functions continuous distributions and soft constraints"
    - "a lambda calculus foundation for universal probabilistic programming"
    - "full abstraction for probabilistic pcf"
    - "church a language for generative models"
    - "probabilistic operational semantics for the lambda calculus"

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.LO(Logic in Computer Science)