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: "inferring covariances for probabilistic programs"
  Abstract: We study weakest precondition reasoning about the (co)variance of outcomes and the variance of run-times of probabilistic programs with conditioning. For outcomes, we show that approximating (co)variances is computationally more difficult than approximating expected values. In particular, we prove that computing both lower and upper bounds for (co)variances is $\Sigma^{0}_{2}$-complete. As a consequence, neither lower nor upper bounds are computably enumerable. We therefore present invariant-based techniques that do enable enumeration of both upper and lower bounds, once appropriate invariants are found. Finally, we extend this approach to reasoning about run-time variances.

Connected through hyperedge HE-1 (induced by source paper "tail probabilities for randomized program runtimes via martingales for higher moments"):
  with members:
    - "probabilistic tools for the analysis of randomized optimization heuristics"
    - "ranking and repulsing supermartingales for reachability in probabilistic programs"
    - "temporal logic verification of stochastic systems using barrier certificates"
    - "how long o bayesian network will i sample thee a program analysis perspective on expected sampling times"
    - "termination of nondeterministic recursive probabilistic programs"
    - "lexicographic ranking supermartingales an efficient approach to termination of probabilistic programs"
    - "categorical liveness checking by corecursive algebras"
    - "design and implementation of probabilistic programming language anglican"

Connected through hyperedge HE-2 (induced by source paper "an assertion based program logic for probabilistic programs"):
  with members:
    - "a new proof rule for almost sure termination"
    - "a new rule for almost certain termination of probabilistic and demonic programs"
    - "a program logic for union bounds"
    - "weakest precondition reasoning for expected run times of probabilistic programs"
    - "synthesizing probabilistic invariants via doob s decomposition"
    - "reasoning about recursive probabilistic programs"
    - "step indexed logical relations for probability"
    - "on probabilistic applicative bisimulation and call by value λ calculi long version"

Connected through hyperedge HE-3 (induced by source paper "bounded model checking for probabilistic programs"):
  with members:
    - "parameter synthesis for markov models faster than ever"
    - "reasoning about recursive probabilistic programs"
    - "high level counterexamples for probabilistic automata"
    - "on the hardness of almost sure termination"

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)