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mesh complexity. Most greedy algorithms utilize local operators [2, 1], or variational approaches [5] or different stages (topology, then geometry) [6], or a larger repertoire of operators [9]. More
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on stochastic Riemannian optimization algorithms, these methods still suffer from limitations in computational complexity. The post-doctoral fellow will build upon this preliminary work to investigate
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revisit discretization methodologies in view of modern requirements and computational capabilities. The candidate will focus on developing mesh generation algorithms meeting the following criteria
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major challenge with dynamic structured data is finding representations that can effectively handle their underlying geometry, which is often defined by application-specific pseudo-distances. A common