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Fast and Flexible Characterisation of Astronomical Light Curves Using Multi-Time Attention
Yash Gondhalekar, Anais Möller, Paula Sánchez-Sáez
We present an unsupervised, data-driven framework for rapid characterisation of astronomical photometric time series using a Multi-Time Attention Network. The model learns time-awa…
Deconvolution for Large Astronomical Surveys: A Study of the Scaled Gradient Projection Method on Zwicky Transient Facility Data
Yash Gondhalekar, Richard M. Feder, Matthew J. Graham +4
Ground-based astronomical observations will continue to produce resolution-limited images due to atmospheric seeing. Deconvolution reverses such effects and thus can benefit extrac…
Convolutional Vision Transformer for Cosmology Parameter Inference
Yash Gondhalekar, Kana Moriwaki
Parameter inference is a crucial task in modern cosmology that requires accurate and fast computational methods to handle the high precision and volume of observational datasets. I…
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…
-SGP: Scaled Gradient Projection with -divergence for astronomical image restoration
Yash Gondhalekar, Margarita Safonova, Snehanshu Saha
Image restoration in astronomy has been considered a vital step in many ground-based observational programs that often suffer from sub-optimal seeing due to atmospheric turbulence,…
The Astropy Project: Sustaining and Growing a Community-oriented Open-source Project and the Latest Major Release (v5.0) of the Core Package
The Astropy Collaboration, Adrian M. Price-Whelan, Pey Lian Lim +133
The Astropy Project supports and fosters the development of open-source and openly-developed Python packages that provide commonly needed functionality to the astronomical communit…
galmask: A Python package for unsupervised galaxy masking
Yash Gondhalekar, Rafael S. de Souza, Ana L. Chies-Santos
Galaxy morphological classification is a fundamental aspect of galaxy formation and evolution studies. Various machine learning tools have been developed for automated pipeline ana…