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foundational and applied topics in computer vision and machine learning, with particular strengths in inverse problems, generative models, and geometric deep learning. We work across diverse application areas
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propagation problems, stochastic partial differential equations, geometric numerical integration, optimization, biomathematics, biostatistics, spatial modeling, Bayesian inference, high-dimensional data, large
Searches related to geometric modelling
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