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: "theano new features and speed improvements"
  Abstract: Theano is a linear algebra compiler that optimizes a user's symbolically-specified mathematical computations to produce efficient low-level implementations. In this paper, we present new features and efficiency improvements to Theano, and benchmarks demonstrating Theano's performance relative to Torch7, a recently introduced machine learning library, and to RNNLM, a C++ library targeted at recurrent neural networks.

Connected through hyperedge HE-1 (induced by source paper "mnn a universal and efficient inference engine"):
  with members:
    - "mlperf inference benchmark"
    - "mobilenets efficient convolutional neural networks for mobile vision applications"
    - "dlvm a modern compiler infrastructure for deep learning systems"
    - "squeezenet alexnet level accuracy with 50x fewer parameters and 0 5mb model size"
    - "xnor net imagenet classification using binary convolutional neural networks"
    - "tensorflow a system for large scale machine learning"
    - "deep residual learning for image recognition"
    - "mxnet a flexible and efficient machine learning library for heterogeneous distributed systems"

Connected through hyperedge HE-2 (induced by source paper "vector representations of text data in deep learning"):
  with members:
    - "rebar low variance unbiased gradient estimates for discrete latent variable models"
    - "starspace embed all the things"
    - "conceptnet 5 5 an open multilingual graph of general knowledge"
    - "swivel improving embeddings by noticing what s missing"
    - "node2vec scalable feature learning for networks"
    - "problems with evaluation of word embeddings using word similarity tasks"
    - "a joint many task model growing a neural network for multiple nlp tasks"
    - "the concrete distribution a continuous relaxation of discrete random variables"

Connected through hyperedge HE-3 (induced by source paper "rlpyt a research code base for deep reinforcement learning in pytorch"):
  with members:
    - "dopamine a research framework for deep reinforcement learning"
    - "an empirical model of large batch training"
    - "accelerated methods for deep reinforcement learning"
    - "horizon facebook s open source applied reinforcement learning platform"
    - "soft actor critic algorithms and applications"
    - "addressing function approximation error in actor critic methods"
    - "distributed prioritized experience replay"
    - "soft actor critic off policy maximum entropy deep reinforcement learning with a stochastic actor"

Connected through hyperedge HE-4 (induced by source paper "pytorchpipe a framework for rapid prototyping of pipelines combining language and vision"):
  with members:
    - "ludwig a type based declarative deep learning toolbox"
    - "leveraging medical visual question answering with supporting facts"
    - "trends in integration of vision and language research a survey of tasks datasets and methods"
    - "mixed precision training for nlp and speech recognition with openseq2seq"
    - "the visual qa devil in the details the impact of early fusion and batch norm on clevr"
    - "object based reasoning in vqa"
    - "pythia v0 1 the winning entry to the vqa challenge 2018"
    - "compositional attention networks for machine reasoning"

Connected through hyperedge HE-5 (induced by source paper "deep learning in the automotive industry recent advances and application examples"):
  with members:
    - "co design of deep neural nets and neural net accelerators for embedded vision applications"
    - "bdd100k a diverse driving video database with scalable annotation tooling"
    - "assessment of deep convolutional neural networks for road surface classification"
    - "an anti fraud system for car insurance claim based on visual evidence"
    - "scalable and accurate deep learning for electronic health records"
    - "deeproad gan based metamorphic autonomous driving system testing"
    - "squeezenext hardware aware neural network design"
    - "an analysis of deep neural network models for practical applications"

Connected through hyperedge HE-6 (induced by source paper "deep node ranking structural network embedding and end to end node classification"):
  with members:
    - "network embedding as matrix factorization unifying deepwalk line pte and node2vec"
    - "graph embedding techniques applications and performance a survey"
    - "attention is all you need"
    - "predicting multicellular function through multi layer tissue networks"
    - "a unified approach to interpreting model predictions"
    - "a survey on network embedding"
    - "personalized pagerank estimation and search a bidirectional approach"
    - "higher order organization of complex networks"

Connected through hyperedge HE-7 (induced by source paper "gluoncv and gluonnlp deep learning in computer vision and natural language processing"):
  with members:
    - "bag of tricks for image classification with convolutional neural networks"
    - "sdnet contextualized attention based deep network for conversational question answering"
    - "simple baselines for human pose estimation and tracking"
    - "bert pre training of deep bidirectional transformers for language understanding"
    - "quo vadis action recognition a new model and the kinetics dataset"
    - "mobilenets efficient convolutional neural networks for mobile vision applications"
    - "mask r cnn"
    - "tensorflow a system for large scale machine learning"

Connected through hyperedge HE-8 (induced by source paper "pznet efficient 3d convnet inference on manycore cpus"):
  with members:
    - "superhuman accuracy on the snemi3d connectomics challenge"
    - "chexnet radiologist level pneumonia detection on chest x rays with deep learning"
    - "efficient processing of deep neural networks a tutorial and survey"
    - "fast and accurate classification of echocardiograms using deep learning"
    - "a survey on deep learning in medical image analysis"
    - "fusionnet a deep fully residual convolutional neural network for image segmentation in connectomics"
    - "the importance of skip connections in biomedical image segmentation"
    - "3d u net learning dense volumetric segmentation from sparse annotation"

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.SC(Symbolic Computation)