74 citations · 92 across the 11 of their papers we have counts for
4 papers · 1 filter
Recall and Refine: A Simple but Effective Source-free Open-set Domain Adaptation Framework
Ismail Nejjar, Hao Dong, Olga Fink
Open-set Domain Adaptation (OSDA) aims to adapt a model from a labeled source domain to an unlabeled target domain, where novel classes - also referred to as target-private unknown…
Efficient Unsupervised Domain Adaptation Regression for Spatial-Temporal Sensor Fusion
Keivan Faghih Niresi, Ismail Nejjar, Olga Fink
The growing deployment of low-cost, distributed sensor networks in environmental and biomedical domains has enabled continuous, large-scale health monitoring. However, these system…
IM-Context: In-Context Learning for Imbalanced Regression Tasks
Ismail Nejjar, Faez Ahmed, Olga Fink
Regression models often fail to generalize effectively in regions characterized by highly imbalanced label distributions. Previous methods for deep imbalanced regression rely on gr…
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…