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Norwegian University of Science and Technology (NTNU)
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Achieving robust neural network performance on non-Euclidean spaces could redefine stability benchmarks in machine learning applications.
Learning dynamics from position data alone not only respects geometric invariants but also excels in noisy environments, paving the way for more robust mechanical system modeling.
