[Paper] Characterization and Photometric Performance of the Hyper Suprime-Cam Software Pipeline
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Updated
Sep 17, 2017 - Jupyter Notebook
[Paper] Characterization and Photometric Performance of the Hyper Suprime-Cam Software Pipeline
How to configure CernVM FS to use LSST binary distribution [won't be updated - please see https://sw.lsst.eu]
Computer Vision library for Astronomy
My simple ML model for Kaggle's PLAsTiCC Astronomical Classification 2018
A tutorial on periodic variable star discrimination using machine learning
Project focused on understanding the fundamental nature of dark matter with LSST
Astro R-CNN: Instance Segmentation in Astronomical Images using Mask R-CNN Deep Learning
Awareness of the signal anomalies in the overscan regions of LSST images is an integral part of obtaining precise signal baselines. This is the code for a primary assessment of overscan anomalies that appear in flat images with long exposure times.
Developing deep learning engines (DLEs) for non-parametric modeling and extracting of information from active galactic nuclei (AGN) light-curves (LCs), which are directly related to the scientific objectives of the LSST Exploring transient optical sky. Developed DLEs Jupyter notebooks might be adaptable for modeling of light-curves of other obje…
Translation and optimisation of SEDMORPH's PawlikMorph IDL code for analysing images of galaxies from SDSS data release 7
Open, versioned taxonomy for astronomical time-series sources
Repository with the tools and scripts for "Robust period estimation using mutual information for multi-band light curves in the synoptic survey era", ApJ, 2017
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