Unverified50% confidenceFactExact time
Traditional methods for uncertainty quantification (UQ) require rerunning the discrete solver for each sample, with computational cost proportional to the number of samples; APTNN's CP decomposition structure allows the network to accept random inputs as additional dimensions, so that a parametric solution mapping is obtained with a single training run.
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50%
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Long-term
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11/6/2026
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