The study addresses heterogeneous UAV cooperative task assignment under complex constraints via an energy learning ...
The ability of computers to learn on their own by using data is known as machine learning. It is closely related to ...
An Ensemble Learning Tool for Land Use Land Cover Classification Using Google Alpha Earth Foundations Satellite Embeddings ...
LAMDA-SSL toolkit delivers the first unified benchmarks and robust algorithms that safely exploit unlabeled data despite ...
Abstract: A hybrid Koopman deep learning algorithm is developed to predict the final synchronization of networked nonlinear dynamics with different topologies merely using neighboring state ...
Abstract: Self-supervised learning (SSL) is a data-driven learning approach that utilizes the innate structure of the data to guide the learning process. In contrast to supervised learning, which ...
The SleepFM model reveals how sleep analysis can predict disease risk, offering insights into sleep's role as a vital health ...
Morning Overview on MSN
Scientists build a ‘periodic table’ for AI models
Scientists are trying to tame the chaos of modern artificial intelligence by doing something very old fashioned: drawing a ...
Engineers and computer scientists are developing AI-powered robots that look and act human. Boston Dynamics invited 60 ...
Introduction Application of artificial intelligence (AI) tools in the healthcare setting gains importance especially in the domain of disease diagnosis. Numerous studies have tried to explore AI in ...
Recent breakthroughs in self-supervised Joint-Embedding Predictive Architectures (JEPAs) have established that regularizing Euclidean representations toward isotropic Gaussian priors yields provable ...
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