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laws and symmetries into architectures like neural operators, physics-informed neural networks (PINNs), and graph-based solvers, the project aims to accelerate simulations in areas including protein
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neural networks. The key challenge? Designing robust and stable numerical schemes that remain efficient even in high dimensions, effectively pushing back against the curse of dimensionality. The ideal
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