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The spectroscopic features of white dwarfs are formed in the thin upper layer of their stellar photosphere. These features carry information about the white dwarf's surface temperature, surface gravity, and chemical composition (hereafter 'labels'). Existing methods to determine these labels rely on complex ab-initio theoretical models, which are not always publicly available. Here, we present two techniques to determine atmospheric labels from white dwarf spectra: a generative fitting pipeline that interpolates theoretical spectra with artificial neural networks and a random forest regression model using parameters derived from absorption line features. We test and compare our methods using a large catalogue of white dwarfs from the Sloan Digital Sky Survey (SDSS), achieving the same accuracy and negligible bias as compared to previous studies. We package our techniques into an open-source python module ' wdtools ' that provides a computationally inexpensive way to determine stellar labels from white dwarf spectra observed from any facility. We will actively develop and update our tool as more theoretical models become publicly available. We discuss applications of our tool in its present form to identify interesting outlier white dwarf systems including those with magnetic fields, helium-rich atmospheres, and double-degenerate binaries. [ABSTRACT FROM AUTHOR]

We present photometric redshifts and associated probability distributions for all detected sources in the Extended Chandra Deep Field South (ECDFS). This work makes use of the most up-to-date data from the Cosmic Assembly Near-IR Deep Legacy Survey (CANDELS) and the Taiwan ECDFS Near-Infrared Survey (TENIS) in addition to other data. We also revisit multi-wavelength counterparts for published X-ray sources from the 4 Ms CDFS and 250 ks ECDFS surveys, finding reliable counterparts for 1207 out of 1259 sources (∼96%). Data used for photometric redshifts include intermediate-band photometry deblended using the TFIT method, which is used for the first time in this work. Photometric redshifts for X-ray source counterparts are based on a new library of active galactic nuclei/galaxy hybrid templates appropriate for the faint X-ray population in the CDFS. Photometric redshift accuracy for normal galaxies is 0.010 and for X-ray sources is 0.014 and outlier fractions are 4% and 5.2%, respectively. The results within the CANDELS coverage area are even better, as demonstrated both by spectroscopic comparison and by galaxy-pair statistics. Intermediate-band photometry, even if shallow, is valuable when combined with deep broadband photometry. For best accuracy, templates must include emission lines. [ABSTRACT FROM AUTHOR]