23 citations · 85 across the 14 of their papers we have counts for
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cs.CV2024★ 2 cited
Uncertainty-Guided Alignment for Unsupervised Domain Adaptation in Regression
Ismail Nejjar, Gaetan Frusque, Florent Forest +1
Unsupervised Domain Adaptation for Regression (UDAR) aims to adapt models from a labeled source domain to an unlabeled target domain for regression tasks. Traditional feature align…
cs.CV2023★ 3 cited
DARE-GRAM : Unsupervised Domain Adaptation Regression by Aligning Inverse Gram Matrices
Ismail Nejjar, Qin Wang, Olga Fink
Unsupervised Domain Adaptation Regression (DAR) aims to bridge the domain gap between a labeled source dataset and an unlabelled target dataset for regression problems. Recent work…