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: "continuously heterogeneous hyper objects in cryo em and 3 d movies of many temporal dimensions"
  Abstract: Single particle cryo-electron microscopy (EM) is an increasingly popular method for determining the 3-D structure of macromolecules from noisy 2-D images of single macromolecules whose orientations and positions are random and unknown. One of the great opportunities in cryo-EM is to recover the structure of macromolecules in heterogeneous samples, where multiple types or multiple conformations are mixed together. Indeed, in recent years, many tools have been introduced for the analysis of multiple discrete classes of molecules mixed together in a cryo-EM experiment. However, many interesting structures have a continuum of conformations which do not fit discrete models nicely; the analysis of such continuously heterogeneous models has remained a more elusive goal. In this manuscript, we propose to represent heterogeneous molecules and similar structures as higher dimensional objects. We generalize the basic operations used in many existing reconstruction algorithms, making our approach generic in the sense that, in principle, existing algorithms can be adapted to reconstruct those higher dimensional objects. As proof of concept, we present a prototype of a new algorithm which we use to solve simulated reconstruction problems.

Connected through hyperedge HE-1 (induced by source paper "hyper molecules on the representation and recovery of dynamical structures with application to flexible macro molecular structures in cryo em"):
  with members:
    - "a representation theory perspective on simultaneous alignment and classification"
    - "non unique games over compact groups and orientation estimation in cryo em"
    - "covariance estimation using conjugate gradient for 3d classification in cryo em"

Connected through hyperedge HE-2 (induced by source paper "heterogeneous multireference alignment a single pass approach"):
  with members:
    - "bispectrum inversion with application to multireference alignment"
    - "painless breakups efficient demixing of low rank matrices"
    - "the sample complexity of multi reference alignment"
    - "a max cut approach to heterogeneity in cryo electron microscopy"
    - "a representation theory perspective on simultaneous alignment and classification"
    - "fundamental limits in multi image alignment"
    - "heterogeneous tensor decomposition for clustering via manifold optimization"
    - "covariance estimation using conjugate gradient for 3d classification in cryo em"

Connected through hyperedge HE-3 (induced by source paper "a representation theory perspective on simultaneous alignment and classification"):
  with members:
    - "message passing algorithms for synchronization problems over compact groups"
    - "heterogeneous multireference alignment a single pass approach"
    - "multisection in the stochastic block model using semidefinite programming"
    - "a max cut approach to heterogeneity in cryo electron microscopy"
    - "the projected power method an efficient algorithm for joint alignment from pairwise differences"
    - "non unique games over compact groups and orientation estimation in cryo em"
    - "covariance estimation using conjugate gradient for 3d classification in cryo em"
    - "multireference alignment using semidefinite programming"

Connected through hyperedge HE-4 (induced by source paper "a max cut approach to heterogeneity in cryo electron microscopy"):
  with members:
    - "a representation theory perspective on simultaneous alignment and classification"
    - "non unique games over compact groups and orientation estimation in cryo em"
    - "covariance estimation using conjugate gradient for 3d classification in cryo em"

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.CV(Computer Vision and Pattern Recognition)