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astro-ph.IM2023
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…
astro-ph.CO2023★ 1 cited
HIDM: Emulating Large Scale HI Maps using Score-based Diffusion Models
Sultan Hassan, Sambatra Andrianomena
Efficiently analyzing maps from upcoming large-scale surveys requires gaining direct access to a high-dimensional likelihood and generating large-scale fields with high fidelity, w…
astro-ph.CO2023
Latent space representations of cosmological fields
Sambatra Andrianomena, Sultan Hassan
We investigate the possibility of learning the representations of cosmological multifield dataset from the CAMELS project. We train a very deep variational encoder on images which…