The strong gravitational lens finding challenge
A&A, 625 (2019) A119
Published online: 2019-05-22
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A comparative study of convolutional neural networks for the detection of strong gravitational lensing
Daniel Magro, Kristian Zarb Adami, Andrea DeMarco, Simone Riggi and Eva SciaccaMonthly Notices of the Royal Astronomical Society 505 (4) 6155 (2021)
https://doi.org/10.1093/mnras/stab1635
Introduction to Gravitational Lensing
Massimo MeneghettiLecture Notes in Physics, Introduction to Gravitational Lensing 956 255 (2021)
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High-quality Strong Lens Candidates in the Final Kilo-Degree Survey Footprint
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Deep forest: Neural network reconstruction of the Lyman-α forest
Lawrence Huang, Rupert A C Croft and Hitesh AroraMonthly Notices of the Royal Astronomical Society 506 (4) 5212 (2021)
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Bayesian deep networks for absolute permeability and porosity uncertainty prediction from image borehole logs from brazilian carbonate reservoirs
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New High-quality Strong Lens Candidates with Deep Learning in the Kilo-Degree Survey
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Optimizing automatic morphological classification of galaxies with machine learning and deep learning using Dark Energy Survey imaging
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MNELLS: the MUSE nearby early-type galaxy lens locator survey
William P Collier, Russell J Smith and John R LuceyMonthly Notices of the Royal Astronomical Society 494 (1) 271 (2020)
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Finding Strong Gravitational Lenses in the DESI DECam Legacy Survey
X. Huang, C. Storfer, V. Ravi, A. Pilon, M. Domingo, D. J. Schlegel, S. Bailey, A. Dey, R. R. Gupta, D. Herrera, S. Juneau, M. Landriau, D. Lang, A. Meisner, J. Moustakas, A. D. Myers, E. F. Schlafly, F. Valdes, B. A. Weaver, J. Yang and C. YècheThe Astrophysical Journal 894 (1) 78 (2020)
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Image Simulations for Strong and Weak Gravitational Lensing
Andrés A. PlazasSymmetry 12 (4) 494 (2020)
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Spin parity of spiral galaxies II: a catalogue of 80 k spiral galaxies using big data from the Subaru Hyper Suprime-Cam survey and deep learning
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Surveying the reach and maturity of machine learning and artificial intelligence in astronomy
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Survey of Gravitationally-lensed Objects in HSC Imaging (SuGOHI)
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Identifying strong lenses with unsupervised machine learning using convolutional autoencoder
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Search for strong galaxy-galaxy lensing in SDSS-III BOSS
Xin-Lun ChengResearch in Astronomy and Astrophysics 20 (1) 002 (2020)
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Deep learning for strong lensing search: tests of the convolutional neural networks and new candidates from KiDS DR3
Zizhao He, Xinzhong Er, Qian Long, et al.Monthly Notices of the Royal Astronomical Society 497 (1) 556 (2020)
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Quantifying the structure of strong gravitational lens potentials with uncertainty-aware deep neural networks
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KiDS-SQuaD
Vladislav Khramtsov, Alexey Sergeyev, Chiara Spiniello, et al.Astronomy & Astrophysics 632 A56 (2019)
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Data Challenges as a Tool for Time-domain Astronomy
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