Neural Active Manifolds: Nonlinear Dimensionality Reduction for Uncertainty Quantification
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We present a new approach for nonlinear dimensionality reduction, specifically designed for computationally expensive mathematical models. We leverage autoencoders to discover a one-dimensional neural active manifold (NeurAM) capturing the model output variabi... ...
