1 citations · 1 across the 6 of their papers we have counts for
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Towards Mitigating Systematics in Large-Scale Surveys via Few-Shot Optimal Transport-Based Feature Alignment
Sultan Hassan, Sambatra Andrianomena, Benjamin D. Wandelt
Systematics contaminate observables, leading to distribution shifts relative to theoretically simulated signals-posing a major challenge for using pre-trained models to label such…
Towards cosmological inference on unlabeled out-of-distribution HI observational data
Sambatra Andrianomena, Sultan Hassan
We present an approach that can be utilized in order to account for the covariate shift between two datasets of the same observable with different distributions. This helps improve…
Towards out-of-distribution generalization in large-scale astronomical surveys: robust networks learn similar representations
Yash Gondhalekar, Sultan Hassan, Naomi Saphra +1
The generalization of machine learning (ML) models to out-of-distribution (OOD) examples remains a key challenge in extracting information from upcoming astronomical surveys. Inter…