The Hilbert–Mumford criterion for representations of network quivers

DOI

10.2991/978-94-6463-330-6_2How to use a DOI?

Keywords

Quiver; representation; neural network; stability; geometric invariant theory; Hilbert–Mumford criterion

Abstract

We give an alternative proof of the characterization of the semistable and the stable framed representations of a network quiver. This is a basic result for understanding the moduli spaces of neural networks which have been recently introduced.

Copyright

© 2023 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Marco A. Armenta
AU  - Alexander H. W. Schmitt
PY  - 2023
DA  - 2023/12/31
TI  - The Hilbert–Mumford criterion for representations of network quivers
BT  - Proceedings of the International Conference on Applied Sciences and Engineering (ICASE 2023)
PB  - Atlantis Press
SP  - 5
EP  - 12
SN  - 2589-4943
UR  - https://doi.org/10.2991/978-94-6463-330-6_2
DO  - 10.2991/978-94-6463-330-6_2
ID  - Armenta2023
ER  -