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 "neural approximation of an auto regressive process through confidence guided sampling"):
  Abstract: We propose a generic confidence-based approximation that can be plugged in and simplify the auto-regressive generation process with a proved convergence. We first assume that the priors of future samples can be generated in an independently and identically distributed (i.i.d.) manner using an efficient predictor. Given the past samples and future priors, the mother AR model can post-process the priors while the accompanied confidence predictor decides whether the current sample needs a resampling or not. Thanks to the i.i.d. assumption, the post-processing can update each sample in a parallel way, which remarkably accelerates the mother model. Our experiments on different data domains including sequences and images show that the proposed method can successfully capture the complex structures of the data and generate the meaningful future samples with lower computational cost while preserving the sequential relationship of the data.

Includes members:
  Member "non autoregressive machine translation with auxiliary regularization":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "parallel machine translation with disentangled context transformer")
  Member "mask predict parallel decoding of conditional masked language models":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "blank language models")
  Member "variational autoencoded regression high dimensional regression of visual data on complex manifold":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a generative map for image based camera localization")
  Member "non monotonic sequential text generation":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "blank language models")
  Member "attentive neural processes":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "local nonparametric meta learning")
  Member "conditional neural processes":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "local nonparametric meta learning")
  Member "blockwise parallel decoding for deep autoregressive models":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "parallel machine translation with disentangled context transformer")
  Member "fast generation for convolutional autoregressive models":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "videoflow a conditional flow based model for stochastic video generation")

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.LG(Machine Learning)