55 citations · 88 across the 4 of their papers we have counts for
11 papers
HOLISMOKES. VI. New galaxy-scale strong lens candidates from the HSC-SSP imaging survey
R. Canameras, S. Schuldt, Y. Shu +8
We have carried out a systematic search for galaxy-scale strong lenses in multiband imaging from the Hyper Suprime-Cam (HSC) survey. Our automated pipeline, based on realistic stro…
Coming Down to Earth: Satellite-to-Street View Synthesis for Geo-Localization
Aysim Toker, Qunjie Zhou, Maxim Maximov +1
The goal of cross-view image based geo-localization is to determine the location of a given street view image by matching it against a collection of geo-tagged satellite images. Th…
Learning Intra-Batch Connections for Deep Metric Learning
Jenny Seidenschwarz, Ismail Elezi, Laura Leal-Taixé
The goal of metric learning is to learn a function that maps samples to a lower-dimensional space where similar samples lie closer than dissimilar ones. Particularly, deep metric l…
Photometric Redshift Estimation with a Convolutional Neural Network: NetZ
S. Schuldt, S. H. Suyu, R. Cañameras +4
The redshifts of galaxies are a key attribute that is needed for nearly all extragalactic studies. Since spectroscopic redshifts require additional telescope and human resources, m…
Deep Shells: Unsupervised Shape Correspondence with Optimal Transport
Marvin Eisenberger, Aysim Toker, Laura Leal-Taixé +1
We propose a novel unsupervised learning approach to 3D shape correspondence that builds a multiscale matching pipeline into a deep neural network. This approach is based on smooth…
HOLISMOKES -- IV. Efficient mass modeling of strong lenses through deep learning
S. Schuldt, S. H. Suyu, T. Meinhardt +4
Modelling the mass distributions of strong gravitational lenses is often necessary to use them as astrophysical and cosmological probes. With the high number of lens systems ($>10^…