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MambaCSP: Hybrid-Attention State Space Models for Hardware-Efficient Channel State Prediction

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Umfang6 Seiten

Online
DOI: 10.48550/arXiv.2604.21957


Einrichtungen

  1. Lehrstuhl für Verteilte Signalverarbeitung (612310)


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Dokumenttyp
Preprint

Format
online

Sprache
English

Externe Identnummern
arXiv: arXiv:2604.21957
OpenAlex: W7155898980

Interne Identnummern
RWTH-2026-08306
Datensatz-ID: 1041017

Beteiligte Länder
Germany

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Related:

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Contribution to a conference proceedings  ;  ;
MambaCSP: Hybrid-Attention State Space Models for Hardware-Efficient Channel State Prediction
43. International Conference on Machine Learning, ICML, SeoulSeoul, South Korea,  GO BibTeX | EndNote: XML, Text | RIS

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 Record created 2026-09-03, last modified 2026-09-11
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