Abstract: Seismic deconvolution is essential for extracting layer information from noisy seismic data, but it is an ill-posed problem with nonunique solutions. Inspired by classical optimization ...
Abstract: This paper investigates multistep and iterative back-door injection in federated learning, revealing how gradual and distributed attacks enhance the persistence and stealth of backdoors.
A tool called AI-Newton can derive scientific laws from raw data, but is some way from developing human-like reasoning.
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