2023
DOI: 10.1051/0004-6361/202244325
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Holismokes

Abstract: Modeling of strong gravitational lenses is a necessity for further applications in astrophysics and cosmology. With the large number of detections in current and upcoming surveys, such as the Rubin Legacy Survey of Space and Time (LSST), it is pertinent to investigate automated and fast analysis techniques beyond the traditional and time-consuming Markov chain Monte Carlo sampling methods. Building upon our (simple) convolutional neural network (CNN), we present here another CNN, specifically a residual neural… Show more

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Cited by 8 publications
(3 citation statements)
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“…(ii) For the algorithms based on a BNN (Perreault Le v asseur et al 2017 ; Bom et al 2019 ;Pearson et al 2021 ;Schuldt et al 2023 ), one of the main differences is the calibration performed on the uncertainties predicted by the network. While the other codes changed the keeprate of the dropout layers to achieve a Gaussian co v erage of the testset, the LEMON algorithm is the only one to employ the a posteriori procedure discussed in Section 4.…”
Section: Comparison With the Literaturementioning
confidence: 99%
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“…(ii) For the algorithms based on a BNN (Perreault Le v asseur et al 2017 ; Bom et al 2019 ;Pearson et al 2021 ;Schuldt et al 2023 ), one of the main differences is the calibration performed on the uncertainties predicted by the network. While the other codes changed the keeprate of the dropout layers to achieve a Gaussian co v erage of the testset, the LEMON algorithm is the only one to employ the a posteriori procedure discussed in Section 4.…”
Section: Comparison With the Literaturementioning
confidence: 99%
“…While the other codes changed the keeprate of the dropout layers to achieve a Gaussian co v erage of the testset, the LEMON algorithm is the only one to employ the a posteriori procedure discussed in Section 4. 2023) Bom et al 2019 ;Schuldt et al 2023 ). These differences strongly impact the dimension of the data sets required to successfully train the algorithms and -therefore -the possibility of training them only by employing the first data provided by Euclid or LSST.…”
Section: Comparison With the Literaturementioning
confidence: 99%
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