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Diehl, I. Sevilla-Noarbe, J. Annis, J. Carretero, J. De Vicente, J. Frieman, J. Garc\\'ia- Bellido, J. Gschwend, J. Zuntz (the DES Collaboration), K. Bechtol, K. Glazebrook, K. Honscheid, K. Kuehn, L. N. da Costa, M. A. G. Maia, M. Carrasco Kind, M. E. C. Swanson, M. Lima, M. Schubnell, M. Smith, M. Soares-Santos, N. Kuropatkin, O. Lahav, P. Doel, P. Martini, R. A. Gruendl, R. Miquel, S. Avila, S. Desai, S. Serrano, T. Collett, T. F. Eifler, T. M. C. Abbott, T. S. Li, V. Scarpine, V. Vikram, W. G. Hartley, Y. Zhang","submitted_at":"2018-11-09T05:59:33Z","abstract_excerpt":"We search Dark Energy Survey (DES) Year 3 imaging data for galaxy-galaxy strong gravitational lenses using convolutional neural networks. We generate 250,000 simulated lenses at redshifts > 0.8 from which we create a data set for training the neural networks with realistic seeing, sky and shot noise. 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