1 code implementation • 15 Jul 2022 • George Stein, Uros Seljak, Vanessa Bohm, G. Aldering, P. Antilogus, C. Aragon, S. Bailey, C. Baltay, S. Bongard, K. Boone, C. Buton, Y. Copin, S. Dixon, D. Fouchez, E. Gangler, R. Gupta, B. Hayden, W. Hillebrandt, M. Karmen, A. G. Kim, M. Kowalski, D. Kusters, P. F. Leget, F. Mondon, J. Nordin, R. Pain, E. Pecontal, R. Pereira, S. Perlmutter, K. A. Ponder, D. Rabinowitz, M. Rigault, D. Rubin, K. Runge, C. Saunders, G. Smadja, N. Suzuki, C. Tao, R. C. Thomas, M. Vincenzi
We construct a physically-parameterized probabilistic autoencoder (PAE) to learn the intrinsic diversity of type Ia supernovae (SNe Ia) from a sparse set of spectral time series.
no code implementations • 3 Jun 2019 • X. Huang, M. Domingo, A. Pilon, V. Ravi, C. Storfer, D. J. Schlegel, S. Bailey, A. Dey, 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, C. Yeche
We compile a training set that consists of known lensing systems in the Legacy Surveys and DES as well as non-lenses in the footprint of DECaLS.
Astrophysics of Galaxies Cosmology and Nongalactic Astrophysics