2 citations · 2 across the 3 of their papers we have counts for
5 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…