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 "futuremapping 2 gaussian belief propagation for spatial ai"):
  Abstract: We argue the case for Gaussian Belief Propagation (GBP) as a strong algorithmic framework for the distributed, generic and incremental probabilistic estimation we need in Spatial AI as we aim at high performance smart robots and devices which operate within the constraints of real products. Processor hardware is changing rapidly, and GBP has the right character to take advantage of highly distributed processing and storage while estimating global quantities, as well as great flexibility. We present a detailed tutorial on GBP, relating to the standard factor graph formulation used in robotics and computer vision, and give several simulation examples with code which demonstrate its properties.

Includes members:
  Member "visual inertial mapping with non linear factor recovery":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "d3vo deep depth deep pose and deep uncertainty for monocular visual odometry")
  Member "scenecode monocular dense semantic reconstruction using learned encoded scene representations":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "routedfusion learning real time depth map fusion")
  Member "codeslam learning a compact optimisable representation for dense visual slam":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "3d point cloud processing and learning for autonomous driving")
  Member "just in time reconstruction inpainting sparse maps using single view depth predictors as priors":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "cam convs camera aware multi scale convolutions for single view depth")
  Member "futuremapping the computational structure of spatial ai systems":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "good feature matching towards accurate robust vo vslam with low latency")
  Member "geometric deep learning going beyond euclidean data":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "a survey on deep geometry learning from a representation perspective")
  Member "distributed mapping with privacy and communication constraints lightweight algorithms and object based models":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "door slam distributed online and outlier resilient slam for robotic teams")
  Member "semanticfusion dense 3d semantic mapping with convolutional neural networks":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "perception and decision making of autonomous systems in the era of learning an overview")

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.AI(Artificial Intelligence)