Corpus ID: 28619568

Towards Grounding Conceptual Spaces in Neural Representations

@article{Bechberger2017TowardsGC,
  title={Towards Grounding Conceptual Spaces in Neural Representations},
  author={Lucas Bechberger and Kai-Uwe K{\"u}hnberger},
  journal={ArXiv},
  year={2017},
  volume={abs/1706.04825}
}
The highly influential framework of conceptual spaces provides a geometric way of representing knowledge. It aims at bridging the gap between symbolic and subsymbolic processing. Instances are represented by points in a high-dimensional space and concepts are represented by convex regions in this space. In this paper, we present our approach towards grounding the dimensions of a conceptual space in latent spaces learned by an InfoGAN from unlabeled data. 
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References

SHOWING 1-10 OF 26 REFERENCES
Conceptual Spaces for Computer Vision Representations
  • 42
  • PDF
Inducing semantic relations from conceptual spaces: A data-driven approach to plausible reasoning
  • 59
  • PDF
Vagueness: A Conceptual Spaces Approach
  • 73
  • PDF
Interpolation and Extrapolation in Conceptual Spaces: A Case Study in the Music Domain
  • 28
  • PDF
Conceptual spaces - the geometry of thought
  • 1,262
  • PDF
Representing part–whole relations in conceptual spaces
  • 31
Representation Learning: A Review and New Perspectives
  • 7,003
  • PDF
Spaces in the Brain: From Neurons to Meanings
  • 14
  • PDF
Anchoring symbols to conceptual spaces: the case of dynamic scenarios
  • 60
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