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 reachability method for verifying dynamical systems with deep neural network controllers"):
  Abstract: Deep neural networks can be trained to be efficient and effective controllers for dynamical systems; however, the mechanics of deep neural networks are complex and difficult to guarantee. This work presents a general approach for providing guarantees for deep neural network controllers over multiple time steps using a combination of reachability methods and open source neural network verification tools. By bounding the system dynamics and neural network outputs, the set of reachable states can be over-approximated to provide a guarantee that the system will never reach states outside the set. The method is demonstrated on the mountain car problem as well as an aircraft collision avoidance problem. Results show that this approach can provide neural network guarantees given a bounded dynamic model.

Includes members:
  Member "algorithms for verifying deep neural networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "parot a practical framework for robust deep neural network training")
  Member "juliareach a toolbox for set based reachability":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "resilient cyberphysical systems and their application drivers a technology roadmap")
  Member "formal security analysis of neural networks using symbolic intervals":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "robustness verification for transformers")
  Member "verisig verifying safety properties of hybrid systems with neural network controllers":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "resilient cyberphysical systems and their application drivers a technology roadmap")
  Member "reachability analysis and safety verification for neural network control systems":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "validation of image based neural network controllers through adaptive stress testing")
  Member "reachable set estimation and verification for neural network models of nonlinear dynamic systems":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "resilient cyberphysical systems and their application drivers a technology roadmap")
  Member "reachable set computation and safety verification for neural networks with relu activations":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "reachability analysis for feed forward neural networks using face lattices")
  Member "evaluating robustness of neural networks with mixed integer programming":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "lossless compression of deep neural networks")

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.SY(Systems and Control)