Quantum-Evolutionary Neural Networks combine phase-shifted sine activations, evolutionary selection, and federated averaging, but the convergence and privacy proofs are asserted rather than derived, and the empirical evidence is too thin to support the stated claims.
Quantum Information Processing22(5), 223 (2023)
1 Pith paper cite this work, alongside 14 external citations. Polarity classification is still indexing.
1
Pith paper citing it
14
external citations · OpenAlex
fields
cs.NE 1years
2025 1verdicts
REJECT 1representative citing papers
citing papers explorer
-
Quantum-Evolutionary Neural Networks for Multi-Agent Federated Learning
Quantum-Evolutionary Neural Networks combine phase-shifted sine activations, evolutionary selection, and federated averaging, but the convergence and privacy proofs are asserted rather than derived, and the empirical evidence is too thin to support the stated claims.