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Max Moebus

2 accepted papers

2025

Contimask: Explaining Irregular Time Series via Perturbations in Continuous Time

NeurIPS 2025poster

Explaining black-box models for time series data is critical for the wide-scale adoption of deep learning techniques across domains such as healthcare. Recently, explainability methods for deep time series models have seen significant progress by adopting saliency methods that perturb masked segment…

Cited by 0SourceScholar
2025

egoPPG: Heart Rate Estimation from Eye-Tracking Cameras in Egocentric Systems to Benefit Downstream Vision Tasks

ICCV 2025poster

Egocentric vision systems aim to understand the spatial surroundings and the wearer's behavior inside it, including motions, activities, and interactions. We argue that egocentric systems must additionally detect physiological states to capture a person's attention and situational responses, which a…

Cited by 0SourcePDFScholar