5k citations · 5k across the 10 of their papers we have counts for
10 papers
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…
Emulation of modified gravity from CDM using conditional GANs
Yash Gondhalekar, Sownak Bose, Baojiu Li +1
A major aim of cosmological surveys is to test deviations from the standard CDM model, but the full scientific value of these surveys will only be realised through efficient sim…
Systematic analysis of jellyfish galaxy candidates in Fornax, Antlia, and Hydra from the S-PLUS survey: A self-supervised visual identification aid
Yash Gondhalekar, Ana L. Chies-Santos, Rafael S. de Souza +22
We study 51 jellyfish galaxy candidates in the Fornax, Antlia, and Hydra clusters. These candidates are identified using the JClass scheme based on the visual classification of wid…
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…
A study of two periodogram algorithms for improving the detection of small transiting planets
Yash Gondhalekar, Eric D. Feigelson, Gabriel A. Caceres +2
The sensitivities of two periodograms are compared for weak signal planet detection in transit surveys: the widely used Box-Least Squares (BLS) algorithm following light curve detr…
-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…