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: "estimating uncertain spatial relationships in robotics"
  Abstract: In this paper, we describe a representation for spatial information, called the stochastic map, and associated procedures for building it, reading information from it, and revising it incrementally as new information is obtained. The map contains the estimates of relationships among objects in the map, and their uncertainties, given all the available information. The procedures provide a general solution to the problem of estimating uncertain relative spatial relationships. The estimates are probabilistic in nature, an advance over the previous, very conservative, worst-case approaches to the problem. Finally, the procedures are developed in the context of state-estimation and filtering theory, which provides a solid basis for numerous extensions.

Connected through hyperedge HE-1 (induced by source paper "two body problem collaborative visual task completion"):
  with members:
    - "tarmac targeted multi agent communication"
    - "understanding grounded language learning agents"
    - "building generalizable agents with a realistic and rich 3d environment"
    - "neural modular control for embodied question answering"
    - "minos multimodal indoor simulator for navigation in complex environments"
    - "unifying map and landmark based representations for visual navigation"
    - "home a household multimodal environment"
    - "learning cooperative visual dialog agents with deep reinforcement learning"

Connected through hyperedge HE-2 (induced by source paper "gen slam generative modeling for monocular simultaneous localization and mapping"):
  with members:
    - "multimodal unsupervised image to image translation"
    - "world models"
    - "crossing nets combining gans and vaes with a shared latent space for hand pose estimation"
    - "a hybrid convolutional variational autoencoder for text generation"
    - "sparse to dense depth prediction from sparse depth samples and a single image"
    - "orb slam2 an open source slam system for monocular stereo and rgb d cameras"
    - "unsupervised learning of depth and ego motion from video"
    - "unsupervised image to image translation networks"

Connected through hyperedge HE-3 (induced by source paper "a probabilistic framework for tracking uncertainties in robotic manipulation"):
  with members:
    - "robust compliant assembly via optimal belief space planning"
    - "touch based object localization in cluttered environments"
    - "planning and resilient execution of policies for manipulation in contact with actuation uncertainty"
    - "on the covariance of x in ax xb"

Connected through hyperedge HE-4 (induced by source paper "characterizing the uncertainty of jointly distributed poses in the lie algebra"):
  with members:
    - "legged robot state estimation through combined forward kinematic and preintegrated contact factors"
    - "on manifold preintegration for real time visual inertial odometry"

Connected through hyperedge HE-5 (induced by source paper "numerical and experimental realization of analytical slam"):
  with members:
    - "simultaneous localization and mapping without linearization"
    - "rao blackwellised particle filtering for dynamic bayesian networks"

Connected through hyperedge HE-6 (induced by source paper "vision based unscented fastslam for mobile robot"):
  with members:
    - "rao blackwellised particle filtering for dynamic bayesian networks"

Connected through hyperedge HE-7 (induced by source paper "active neural localization"):
  with members:
    - "vidloc a deep spatio temporal model for 6 dof video clip relocalization"
    - "vinet visual inertial odometry as a sequence to sequence learning problem"
    - "domain randomization for transferring deep neural networks from simulation to the real world"
    - "neural map structured memory for deep reinforcement learning"
    - "airsim high fidelity visual and physical simulation for autonomous vehicles"
    - "deepvo towards end to end visual odometry with deep recurrent convolutional neural networks"
    - "qmdp net deep learning for planning under partial observability"
    - "cosine normalization using cosine similarity instead of dot product in neural networks"

Connected through hyperedge HE-8 (induced by source paper "contact aided invariant extended kalman filtering for legged robot state estimation"):
  with members:
    - "rins w robust inertial navigation system on wheels"
    - "closed form preintegration methods for graph based visual inertial navigation"
    - "hybrid contact preintegration for visual inertial contact state estimation using factor graphs"
    - "robocentric visual inertial odometry"
    - "feedback control of a cassie bipedal robot walking standing and riding a segway"
    - "vins mono a robust and versatile monocular visual inertial state estimator"
    - "invariant smoothing on lie groups"
    - "on manifold preintegration for real time visual inertial odometry"

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.AI(Artificial Intelligence)