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PG-KINN outperforms legacy approaches by leveraging a Petrov-Galerkin framework, achieving robust solutions for complex PDEs with improved accuracy and interpretability.
Achieving up to 28% power reduction, this new multiplier redefines efficiency in modular arithmetic for RNS, crucial for high-performance computing tasks.
Ditch the Transformers: a cleverly designed all-MLP architecture, ITS-Mina, rivals state-of-the-art time series forecasting while slashing computational costs.
