We present a set of low resolution empirical SED templates for AGNs and galaxies in the wavelength range from 0.03 to 30 microns based on the multi-wavelength photometric observations of the NOAO Deep-Wide Field Survey Bootes field and the spectroscopic observations of the AGN and Galaxy Evolution Survey. Our training sample is comprised of 14448 galaxies in the redshift range 0<~z<~1 and 5347 likely AGNs in the range 0<~z<~5.58. We use our templates to determine photometric redshifts for galaxies and AGNs. While they are relatively accurate for galaxies, their accuracies for AGNs are a strong function of the luminosity ratio between the AGN and galaxy components. Somewhat surprisingly, the relative luminosities of the AGN and its host are well determined even when the photometric redshift is significantly in error. We also use our templates to study the mid-IR AGN selection criteria developed by Stern et al.(2005) and Lacy et al.(2004). We find that the Stern et al.(2005) criteria suffers from significant incompleteness when there is a strong host galaxy component and at z =~ 4.5, when the broad Halpha emission line is redshifted into the [3.6] band, but that it is little contaminated by low and intermediate redshift galaxies. The Lacy et al.(2004) criterion is not affected by incompleteness at z =~ 4.5 and is somewhat less affected by strong galaxy host components, but is heavily contaminated by low redshift star forming galaxies. Finally, we use our templates to predict the color-color distribution of sources in the upcoming WISE mission and define a color criterion to select AGNs analogous to those developed for IRAC photometry. We estimate that in between 640,000 and 1,700,000 AGNs will be identified by these criteria, but will have serious completeness problems for z >~ 3.4.

UPSILoN (AUtomated Classification of Periodic Variable Stars using MachIne LearNing) classifies periodic variable stars such as Delta Scuti stars, RR Lyraes, Cepheids, Type II Cepheids, eclipsing binaries, and long-period variables (i.e. superclasses), and their subclasses (e.g. RR Lyrae ab, c, d, and e types) using well-sampled light curves from any astronomical time-series surveys in optical bands regardless of their survey-specific characteristics such as color, magnitude, and sampling rate. UPSILoN consists of two parts, one which extracts variability features from a light curve, and another which classifies a light curve, and returns extracted features, a predicted class, and a class probability. In principle, UPSILoN can classify any light curves having arbitrary number of data points, but using light curves with more than ~80 data points provides the best classification quality.

Jdaviz provides data viewers and analysis plugins that can be flexibly combined as desired to create interactive applications. It offers Specviz (ascl:1902.011) for visualization and quick-look analysis of 1D astronomical spectra; Mosviz for visualization of astronomical spectra, including 1D and 2D spectra as well as contextual information, and Cubeviz for visualization of spectroscopic data cubes (such as those produced by JWST MIRI). Imviz, which provides visualization and quick-look analysis for 2D astronomical images, is also included. Jdaviz is designed with instrument modes from the James Webb Space Telescope (JWST) in mind, but the tool is flexible enough to read in data from many astronomical telescopes, and the documentation provides a complete table of all supported modes.