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 "augmenting physical simulators with stochastic neural networks case study of planar pushing and bouncing"):
  Abstract: An efficient, generalizable physical simulator with universal uncertainty estimates has wide applications in robot state estimation, planning, and control. In this paper, we build such a simulator for two scenarios, planar pushing and ball bouncing, by augmenting an analytical rigid-body simulator with a neural network that learns to model uncertainty as residuals. Combining symbolic, deterministic simulators with learnable, stochastic neural nets provides us with expressiveness, efficiency, and generalizability simultaneously. Our model outperforms both purely analytical and purely learned simulators consistently on real, standard benchmarks. Compared with methods that model uncertainty using Gaussian processes, our model runs much faster, generalizes better to new object shapes, and is able to characterize the complex distribution of object trajectories.

Includes members:
  Member "fundamental limitations in performance and interpretability of common planar rigid body contact models":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "making sense of vision and touch learning multimodal representations for contact rich tasks")
  Member "combining learned and analytical models for predicting action effects":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "omnipush accurate diverse real world dataset of pushing dynamics with rgb d video")
  Member "stochastic variational video prediction":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "transformation based adversarial video prediction on large scale data")
  Member "a fast stochastic contact model for planar pushing and grasping theory and experimental validation":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "let s push things forward a survey on robot pushing")
  Member "gp sum gaussian processes filtering of non gaussian beliefs":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "omnipush accurate diverse real world dataset of pushing dynamics with rgb d video")
  Member "learning data efficient rigid body contact models case study of planar impact":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "fundamental limitations in performance and interpretability of common planar rigid body contact models")
  Member "a probabilistic data driven model for planar pushing":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "let s push things forward a survey on robot pushing")
  Member "experimental validation of contact dynamics for in hand manipulation":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "let s push things forward a survey on robot pushing")

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.RO(Robotics)