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 "traphic trajectory prediction in dense and heterogeneous traffic using weighted interactions"):
  Abstract: We present a new algorithm for predicting the near-term trajectories of road-agents in dense traffic videos. Our approach is designed for heterogeneous traffic, where the road-agents may correspond to buses, cars, scooters, bicycles, or pedestrians. We model the interactions between different road-agents using a novel LSTM-CNN hybrid network for trajectory prediction. In particular, we take into account heterogeneous interactions that implicitly accounts for the varying shapes, dynamics, and behaviors of different road agents. In addition, we model horizon-based interactions which are used to implicitly model the driving behavior of each road-agent. We evaluate the performance of our prediction algorithm, TraPHic, on the standard datasets and also introduce a new dense, heterogeneous traffic dataset corresponding to urban Asian videos and agent trajectories. We outperform state-of-the-art methods on dense traffic datasets by 30%.

Includes members:
  Member "predicting motion of vulnerable road users using high definition maps and efficient convnets":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "densecavoid real time navigation in dense crowds using anticipatory behaviors")
  Member "how would surround vehicles move a unified framework for maneuver classification and motion prediction":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "social wagdat interaction aware trajectory prediction via wasserstein graph double attention network")
  Member "autorvo local navigation with dynamic constraints in dense heterogeneous traffic":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "inner attention supported adaptive cooperation for heterogeneous multi robots teaming based on multi agent reinforcement learning")
  Member "convolutional social pooling for vehicle trajectory prediction":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "sequential forecasting of 100 000 points")
  Member "social gan socially acceptable trajectories with generative adversarial networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "dlow diversifying latent flows for diverse human motion prediction")
  Member "identifying driver behaviors using trajectory features for vehicle navigation":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "cmetric a driving behavior measure using centrality functions")
  Member "short term motion prediction of traffic actors for autonomous driving using deep convolutional networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "laserflow efficient and probabilistic object detection and motion forecasting")
  Member "object detection with deep learning a review":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "when deep learning meets data alignment a review on deep registration networks drns")

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)