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 "correctness of sequential monte carlo inference for probabilistic programming languages"):
  Abstract: Probabilistic programming languages (PPLs) make it possible to reason under uncertainty, by encoding inference problems as programs. In order to solve these inference problems, PPLs employ many different inference algorithms. Existing research on such inference algorithms mainly concerns their implementation and efficiency, rather than the correctness of the algorithms themselves when applied in the context of expressive PPLs. To remedy this, we give a correctness proof for sequential Monte Carlo (SMC) methods in the context of an expressive PPL calculus, representative of popular PPLs such as WebPPL, Anglican, and Birch. Previous work have studied correctness of Markov chain Monte Carlo (MCMC) using an operational semantics, and in a denotational setting without term recursion. However, for SMC inference---one of the most commonly used algorithms in PPLs as of today---no formal correctness proof exists in an untyped operational setting. In particular, an open question is if the resample locations in a probabilistic program affects the correctness of SMC. We solve this fundamental problem, and make three novel contributions: (i) we prove, for the first time, that SMC inference is correct in an untyped operational context of an expressive PPL calculus, and we show that, under mild assumptions, the correctness is independent of the placement of explicit resampling points, (ii) we formalize the bootstrap particle filter for the calculus, and (iii) we demonstrate a classical law of large numbers from the SMC literature that holds as a consequence of our proof.

Includes members:
  Member "a domain theory for statistical probabilistic programming":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "on the linear structure of cones")
  Member "denotational validation of higher order bayesian inference":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "towards verified stochastic variational inference for probabilistic programs")
  Member "design and implementation of probabilistic programming language anglican":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "stochastically differentiable probabilistic programs")
  Member "coarse to fine sequential monte carlo for probabilistic programs":
    also connected through other hyperedges:
      (none)

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.PL(Programming Languages)