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.
Journal of Machine Learning Research (JMLR)24, 1–24 (2023), https://www.jmlr.org/papers/volume24/2023/2023 evolutionary.pdf
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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.