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: "hierarchical temporal memory based on spin neurons and resistive memory for energy efficient brain inspired computing"
  Abstract: Hierarchical temporal memory (HTM) tries to mimic the computing in cerebral neocortex. It identifies spatial and temporal patterns in the input for making inferences. This may require a large number of computationally expensive tasks, such as dot product evaluations. Nanodevices that can provide direct mapping for such primitives are of great interest. In this paper, we propose that the computing blocks for HTM can be mapped using low-voltage, magnetometallic spin-neurons combined with an emerging resistive crossbar network, which involves a comprehensive design at algorithm, architecture, circuit, and device levels. Simulation results show the possibility of more than    $200\times$    lower energy as compared with a 45-nm CMOS ASIC design.

Connected through hyperedge HE-1 (induced by source paper "hierarchical temporal memory using memristor networks a survey"):
  with members:
    - "feature extraction without learning in an analog spatial pooler memristive cmos circuit design of hierarchical temporal memory"
    - "on chip face recognition system design with memristive hierarchical temporal memory"
    - "a survey of memristive threshold logic circuits"
    - "non volatile hierarchical temporal memory hardware for spatial pooling"
    - "continuous online sequence learning with an unsupervised neural network model"

Connected through hyperedge HE-2 (induced by source paper "binary weighted memristive analog deep neural network for near sensor edge processing"):
  with members:
    - "hierarchical temporal memory using memristor networks a survey"
    - "feature extraction without learning in an analog spatial pooler memristive cmos circuit design of hierarchical temporal memory"

Connected through hyperedge HE-3 (induced by source paper "approximate probabilistic neural networks with gated threshold logic"):
  with members:
    - "hierarchical temporal memory using memristor networks a survey"

Connected through hyperedge HE-4 (induced by source paper "on chip face recognition system design with memristive hierarchical temporal memory"):
  with members:
    - "a survey of memristive threshold logic circuits"

Connected through hyperedge HE-5 (induced by source paper "non volatile hierarchical temporal memory hardware for spatial pooling"):
  with members:
    - "claasic a cortex inspired hardware accelerator"
    - "continuous online sequence learning with an unsupervised neural network model"
    - "training and operation of an integrated neuromorphic network based on metal oxide memristors"

Connected through hyperedge HE-6 (induced by source paper "stt snn a spin transfer torque based soft limiting non linear neuron for low power artificial neural networks"):
  with members:
    - "design and synthesis of ultralow energy spin memristor threshold logic"

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.ET(Emerging Technologies)