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 "no representation without transformation"):
  Abstract: We propose to extend Latent Variable Models with a simple idea: learn to encode not only samples but also transformations of such samples. This means that the latent space is not only populated by embeddings but also by higher order objects that map between these embeddings. We show how a hierarchical graphical model can be utilized to enforce desirable algebraic properties of such latent mappings. These mappings in turn structure the latent space and hence can have a core impact on downstream tasks that are solved in the latent space. We demonstrate this impact on a set of experiments and also show that the representation of these latent mappings reflects interpretable properties.

Includes members:
  Member "learning to discover novel visual categories via deep transfer clustering":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "automatically discovering and learning new visual categories with ranking statistics")
  Member "unsupervised learning of object keypoints for perception and control":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "entity abstraction in visual model based reinforcement learning")
  Member "dynamics aware unsupervised discovery of skills":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "intelligence physics and information the tradeoff between accuracy and simplicity in machine learning")
  Member "temporal cycle consistency learning":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "blurry video frame interpolation")
  Member "shaping belief states with generative environment models for rl":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "the next decade in ai four steps towards robust artificial intelligence")
  Member "neural processes":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "modelling latent skills for multitask language generation")
  Member "neural predictive belief representations":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "dream to control learning behaviors by latent imagination")
  Member "challenging common assumptions in the unsupervised learning of disentangled representations":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "nestedvae isolating common factors via weak supervision")

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)