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Abstract: We develop a framework for estimating unknown partial differential equations (PDEs) from noisy data, using a deep learning approach. Given noisy samples of a solution to an unknown PDE, our ...
Abstract: In this paper, we propose an automatic tool to search for optimal differential and linear trails in ARX ciphers. It’s shown that a modulo addition can be divided into sequential small modulo ...
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