Domain adaptation with an ensemble of CNN and transformer models trained on DES detects 20,180 LSBGs and 434 UDGs in KiDS DR5, with structural parameters and environmental trends consistent with known samples.
H., et al
5 Pith papers cite this work, alongside 468 external citations. Polarity classification is still indexing.
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representative citing papers
LSST will image 18,000 square degrees of sky about 800 times across six bands over 10 years to a coadded depth of r~27.5, producing a public database of 40 billion objects and 32 trillion observations.
Composite time-delay lens modelling of JWST WFI2033–4723 yields intermediate stellar IMF normalisation and a steep gNFW inner slope γ_in≃1.3 that is robust to the choice of external cosmology.
GIGA-Lens 2.0 scales strong gravitational lens modeling across up to 128 GPU nodes and demonstrates it on 100 simulated systems plus one real DESI lens.
A convLSTM classifier identifies lensed SNe Ia in simulated LSST-like time series, reaching ~60% true-positive rate at O(10^{-4}) false-positive rate by the seventh epoch even after adding realistic PSF variations and foreground SN contaminants.
citing papers explorer
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From DES to KiDS: Domain adaptation for cross-survey detection of low-surface-brightness galaxies
Domain adaptation with an ensemble of CNN and transformer models trained on DES detects 20,180 LSBGs and 434 UDGs in KiDS DR5, with structural parameters and environmental trends consistent with known samples.
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LSST: from Science Drivers to Reference Design and Anticipated Data Products
LSST will image 18,000 square degrees of sky about 800 times across six bands over 10 years to a coadded depth of r~27.5, producing a public database of 40 billion objects and 32 trillion observations.
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Disentangling the dark and stellar mass through precise lens modelling of the JWST observation of lensed quasar WFI2033--4723
Composite time-delay lens modelling of JWST WFI2033–4723 yields intermediate stellar IMF normalisation and a steep gNFW inner slope γ_in≃1.3 that is robust to the choice of external cosmology.
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GIGA-Lens 2.0: Strong-Lens Modeling on Multiple GPU Nodes
GIGA-Lens 2.0 scales strong gravitational lens modeling across up to 128 GPU nodes and demonstrates it on 100 simulated systems plus one real DESI lens.
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HOLISMOKES XXI: Detecting strongly lensed type Ia supernovae from time series of multi-band LSST-like imaging data -- Part II
A convLSTM classifier identifies lensed SNe Ia in simulated LSST-like time series, reaching ~60% true-positive rate at O(10^{-4}) false-positive rate by the seventh epoch even after adding realistic PSF variations and foreground SN contaminants.