Abstract: A novel meshless electromagnetic (EM) simulation framework based on Physics-Informed Neural Networks (PINNs), enhanced by the integration of Kolmogorov–Arnold Networks (KANs) is presented.
Uncertainty-Aware Flood Inundation Mapping With a Bayesian Deep Learning Framework Using SAR Imagery
Abstract: Climate change-induced extreme rainfall events are driving a rise in flood frequency, posing significant challenges that need to be addressed by decision-makers. To aid in this challenge, ...
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We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors ...
Artificial intelligence (AI) has rapidly become the focal point of global governmental attention and investment. Nations are launching AI for science strategies on a scale comparable to historic ...
It’s been three-and-a-half years since generative AI exploded onto the scene. In this past year, progress has continued its relentless pace: Vibe coding took off, companies embraced agentic workflows, ...
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