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MambaCSP: Hybrid-Attention State Space Models for Hardware-Efficient Channel State Prediction
; ;
2026
Online
DOI: 10.48550/arXiv.2604.21957
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Fulltext by arXiv.org
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
Related:
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,
(2026)
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Fulltext by arXiv.org