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News/Geodesic Flow Matching for Denoising High-Dimensional Structured Representations
arxiv
PublishedJune 2, 2026 at 4:00 AM
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Geodesic Flow Matching for Denoising High-Dimensional Structured Representations

Source
arxiv.orgfull article ↗
Read on arxiv→
Publisher summary· verbatim

arXiv:2606.00248v1 Announce Type: new Abstract: Vector Symbolic Algebras (VSAs) enable robust neurosymbolic reasoning by encoding symbolic information into high-dimensional distributed representations. For continuous domains, Spatial Semantic Pointers (SSPs) extend this framework by mapping variable

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Discussion
Mentioned models
02
  • 01
    Spatial Semantic Pointers (SSPs)
  • 02
    Geodesic Flow Matching
Source
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arxiv
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Tags
04
#neurosymbolic#spiking-neural#geometry#slam

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Mentioned models
02
  • 01
    Spatial Semantic Pointers (SSPs)
  • 02
    Geodesic Flow Matching
Source
↗
arxiv
Read original ↗All from arxiv →
Tags
04
#neurosymbolic#spiking-neural#geometry#slam

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arxivVeriEvolve: Evaluator-First Evolution for Tool-Using Agents1darxivTNODEV: Toolbox for Neural ODE Verification1darxivLearning to Interfere in Non-Orthogonal Multiple-Access Joint Source-Channel Coding1darxivOn the Expressive Power and Limitations of Multi-Layer SSMs1d
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