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: "dynamic bayesian networks as formal abstractions of structured stochastic processes"
  Abstract: We study the problem of finite-horizon probabilistic invariance for discrete-time Markov processes over general (uncountable) state spaces. We compute discrete-time, finite-state Markov chains as formal abstractions of general Markov processes. Our abstraction differs from existing approaches in two ways. First, we exploit the structure of the underlying Markov process to compute the abstraction separately for each dimension. Second, we employ dynamic Bayesian networks (DBN) as compact representations of the abstraction. In contrast, existing approaches represent and store the (exponentially large) Markov chain explicitly, which leads to heavy memory requirements limiting the application to models of dimension less than half, according to our experiments. We show how to construct a DBN abstraction of a Markov process satisfying an independence assumption on the driving process noise. We compute a guaranteed bound on the error in the abstraction w.r.t.\ the probabilistic invariance property; the dimension-dependent abstraction makes the error bounds more precise than existing approaches. Additionally, we show how factor graphs and the sum-product algorithm for DBNs can be used to solve the finite-horizon probabilistic invariance problem. Together, DBN-based representations and algorithms can be significantly more efficient than explicit representations of Markov chains for abstracting and model checking structured Markov processes.

Connected through hyperedge HE-1 (induced by source paper "compositional abstraction based synthesis of general mdps via approximate probabilistic relations"):
  with members:
    - "temporal logic control of general markov decision processes by approximate policy refinement"
    - "robust dynamic programming for temporal logic control of stochastic systems"
    - "compositional construction of infinite abstractions for networks of stochastic control systems"
    - "compositional abstractions of interconnected discrete time stochastic control systems"
    - "from dissipativity theory to compositional construction of finite markov decision processes"
    - "compositional synthesis of finite state abstractions"

Connected through hyperedge HE-2 (induced by source paper "compositional in finite abstractions for large scale interconnected stochastic systems"):
  with members:
    - "compositional abstraction based synthesis of general mdps via approximate probabilistic relations"
    - "compositional construction of infinite abstractions for networks of stochastic control systems"
    - "compositional abstractions of interconnected discrete time stochastic control systems"
    - "from dissipativity theory to compositional synthesis of symbolic models"
    - "compositional abstraction and safety synthesis using overlapping symbolic models"
    - "from dissipativity theory to compositional construction of finite markov decision processes"

Connected through hyperedge HE-3 (induced by source paper "compositional construction of infinite abstractions for networks of stochastic control systems"):
  with members:
    - "robust dynamic programming for temporal logic control of stochastic systems"
    - "compositional in finite abstractions for large scale interconnected stochastic systems"
    - "compositional abstractions of interconnected discrete time stochastic control systems"
    - "compositional construction of finite state abstractions for stochastic control systems"
    - "from dissipativity theory to compositional construction of finite markov decision processes"

Connected through hyperedge HE-4 (induced by source paper "temporal logic verification of stochastic systems using barrier certificates"):
  with members:
    - "from dissipativity theory to compositional construction of finite markov decision processes"
    - "faust 2 f ormal abstractions of uncountable state stochastic processes"
    - "automata theory meets barrier certificates temporal logic verification of nonlinear systems"

Connected through hyperedge HE-5 (induced by source paper "from dissipativity theory to compositional construction of finite markov decision processes"):
  with members:
    - "compositional construction of infinite abstractions for networks of stochastic control systems"
    - "compositional abstractions of interconnected discrete time stochastic control systems"
    - "compositional construction of finite state abstractions for stochastic control systems"
    - "compositional abstraction and safety synthesis using overlapping symbolic models"

Connected through hyperedge HE-6 (induced by source paper "compositional construction of finite state abstractions for stochastic control systems"):
  with members:
    - "compositional synthesis of finite state abstractions"

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.SY(Systems and Control)