UQ-SHRED: uncertainty quantification of shallow recurrent decoder networks for sparse sensing via engression

UQ-SHRED: uncertainty quantification of shallow recurrent decoder networks for sparse sensing via engression explores UQ-SHRED quantifies uncertainty in reconstructing complex spatiotemporal fields from sparse sensor data using a novel distributional regression approach.. Commercial viability score: 7/10 in Scientific AI.