2 papers
cs.LG2026
Rapid Augmentations for Time Series (RATS): A High-Performance Library for Time Series Augmentation
Wadie Skaf, Felix Kern, Aryamaan Basu Roy +3
Time series augmentation is critical for training robust deep learning models, particularly in domains where labelled data is scarce and expensive to obtain. However, existing augm…
cs.CV2025
Mitigating representation bias caused by missing pixels in methane plume detection
Julia WÄ sala, Joannes D. Maasakkers, Ilse Aben +3
Most satellite images have systematically missing pixels (i.e., missing data not at random (MNAR)) due to factors such as clouds. If not addressed, these missing pixels can lead to…