Braid-based architecture search
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Abstract (arXiv)
In this article, we propose the approach to structural optimization of neural networks, based on the braid theory. The paper describes the basics of braid theory as applied to the description of graph structures of neural networks. It is shown how networks of various topologies can be built using braid structures between layers of neural networks. The operation of a neural network based on the braid theory is compared with a homogeneous deep neural network and a network with random intersections between layers that do not correspond to the ordering of the braids. Results are obtained showing the advantage of braid-based networks over comparable architectures in classification problems.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 5 of its 11 references that are in the map. First posted on arXiv 8 Jul 2022.
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5 of 11 references.
References · 5
- 2016Neural Architecture Search with Reinforcement Learningcited by 1,499
- 2017PathNet: Evolution Channels Gradient Descent in Super Neural Networkscited by 364
- 2016Designing Neural Network Architectures using Reinforcement Learningcited by 279
- 2016Convolutional Neural Fabricscited by 32
- 2017Learning Time/Memory-Efficient Deep Architectures with Budgeted Super Networkscited by 4
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