Classifying Image Sequences of Astronomical Transients with Deep Neural Networks
Universidad de los Andes（洛斯安第斯大学）；Center for Research and Formation in Artificial Intelligence（人工智能研究与培训中心）；Systems and Computing Engineering Department（系统与计算工程系）；Departamento de Física（物理系）
Catalina Gómez, Mauricio Neira, Marcela Hernández Hoyos, Pablo Arbeláez, Jaime E. Forero-Romero
Supervised classification of temporal sequences of astronomical images into meaningful transient astrophysical phenomena has been considered a hard problem because it requires the intervention of human experts. The classifier uses the expert's knowledge to find heuristic features to process the images, for instance, by performing image subtraction or by extracting sparse information such as flux time series, also known as light curves. We present a successful deep learning approach that learns directly from imaging data. Our method models explicitly the spatio-temporal patterns with Deep Convolutional Neural Networks and Gated Recurrent Units. We train these deep neural networks using 1.3 million real astronomical images from the Catalina Real-Time Transient Survey to classify the sequences into five different types of astronomical transient classes. The TAO-Net (for Transient Astronomical Objects Network) architecture outperforms the results from random forest classification on light curves by 10 percentage points as measured by the F1 score for each class; the average F1 over classes goes from $45\%$ with random forest classification to $55\%$ with TAO-Net. This achievement with TAO-Net opens the possibility to develop new deep learning architectures for early transient detection. We make available the training dataset and trained models of TAO-Net to allow for future extensions of this work.
Feature Selection Strategies for Classifying High Dimensional Astronomical Data Sets
Jet Propulsion Laboratory（喷气推进实验室）；California Institute of Technology（加州理工学院）；Graduate Institute of Astronomy, NCU（国立中央大学天文研究所）；St. Thomas College（圣托马斯学院）；Università degli Studi Federico II（费德里科二世大学）
Machine Learning Supports Existence of Previously Unrecognized Transient Astronomical Phenomena in Historical Observatory Images
Vanderbilt University Medical Center（范德堡大学医学中心）；Independent Researcher（独立研究者）；Instituto de Astrofísica de Canarias（加那利群岛天体物理研究所）；Nordita, KTH Royal Institute of Technology and Stockholm University（诺迪塔，皇家理工学院和斯德哥尔摩大学）
Temporal Stamp Classifier: Classifying Short Sequences of Astronomical Alerts
Universidad de Chile（智利大学）；Millennium Institute of Astrophysics（千年天体物理学研究所）；Data and Artificial Intelligence Initiative (IDIA), Universidad de Chile（智利大学数据与人工智能计划（IDIA））；Center for Mathematical Modeling (CMM), Universidad de Chile（智利大学数学建模中心（CMM））
FIP-TOI: Fast Imaging Pipeline for Pulsar Localisation with a Transient-Oriented Radio Astronomical Imager
University of Oxford（牛津大学）；Silesian University in Opava（奥帕瓦西里西亚大学）；Mila - Québec Artificial Intelligence Institute（米拉-魁北克人工智能研究所）；University of Cambridge（剑桥大学）；Special Astrophysical Observatory of the Russian Academy of Sciences（俄罗斯科学院特别天体物理观测站）
Real-time Detection of Anomalies in Multivariate Time Series of Astronomical Data
Massachusetts Institute of Technology（麻省理工学院）；University of Cambridge（剑桥大学）；University of the Western Cape（西开普大学）；South African Radio Astronomy Observatory（南非射电天文台）；Swinburne University of Technology（斯威本科技大学）；University of Illinois at Urbana-Champaign（伊利诺伊大学厄巴纳-香槟分校）
Website with interactive visualization of multivariate astronomical time series
Yandex LLC（Yandex公司）；Max-Planck-Institut für Astronomie（马克斯·普朗克天文学研究所）；Heidelberg University（海德堡大学）；Sternberg Astronomical Institute, Moscow M.V. Lomonosov State University（莫斯科罗蒙诺索夫国立大学斯特恩伯格天文研究所）；Université Paris Cité, CNRS(/IN2P3), Astroparticule et Cosmologie（巴黎西岱大学，法国国家科学研究中心/法国核能与替代能源委员会，亚原子粒子与宇宙学实验室）；Center for Astrophysics — Harvard and Smithsonian（哈佛-史密森尼天体物理中心）
A Classifier-Based Approach to Multi-Class Anomaly Detection for Astronomical Transients
Irvington High School（欧文顿高中）；University of the Western Cape（西开普大学）；South African Radio Astronomy Observatory（南非射电天文观测台）；Massachusetts Institute of Technology（麻省理工学院）
Transformer-Based Neural Network for Transient Detection without Image Subtraction
Department of Physics and Astronomy, University of Pennsylvania（物理与天文学系，宾夕法尼亚大学）；Department of Physics and Astronomy, University of Delaware（物理与天文学系，德克萨斯大学）；University of Delaware, Joseph R. Biden, Jr. School of Public Policy and Administration（德克萨斯大学乔伊斯·拜登初级公共政策与行政学校）；University of Delaware, Data Science Institute（德克萨斯大学数据科学研究所）
Active learning with RESSPECT: Resource allocation for extragalactic astronomical transients
Department of Computer Science University of California Irvine（加利福尼亚大学尔湾分校计算机科学系）；Université Clermont Auvergne CNRS/IN2P3, LPC Clermont Ferrand（克莱蒙费朗大学（Université Clermont Auvergne）、法国国家科学研究中心/法国国家核物理与粒子物理研究所（CNRS/IN2P3）、克莱蒙费朗物理实验室（LPC Clermont Ferrand））；CENTRA-Centro de Astrofísica e Gravitação Universidade de Lisboa（里斯本大学（Universidade de Lisboa）中心天体物理与引力中心（CENTRA-Centro de Astrofísica e Gravitação））；Shanghai Astronomical Observatory Chinese Academy of Sciences（中国科学院上海天文台）；Berkeley Center for Cosmological Physics University of California Berkeley（加利福尼亚大学伯克利分校宇宙物理伯克利中心）；Department of Computer Science University of Houston（休斯顿大学计算机科学系）；Department of Physics and Astronomy The Johns Hopkins University（约翰斯·霍普金斯大学物理与天文系）；Department of Informatics University of California Irvine（加利福尼亚大学尔湾分校信息学系）；NSF’s NOIRLab（美国国家科学基金会国家光学红外天文学研究实验室（NOIRLab））；Gemini Observatory（双子座天文台）
Deep-HiTS: Rotation Invariant Convolutional Neural Network for Transient Detection
Millennium Institute of Astrophysics（千年天体物理研究所）；Center for Mathematical Modeling, Universidad de Chile（智利大学数学建模中心）；AURA Observatory in Chile（智利AURA天文台）；Universidad de Chile（智利大学）
Machine Learning Classification of SDSS Transient Survey Images
University of Cape Town（开普敦大学）；African Institute for Mathematical Sciences（非洲数学科学研究所）；South African Astronomical Observatory（南非天文台）；University of the Western Cape（西开普大学）；University of Southampton（南安普顿大学）
StarWhisper Telescope: An AI framework for automating end-to-end astronomical observations
University of Chinese Academy of Sciences（中国科学院大学）；Key Laboratory of Optical Astronomy National Astronomical Observatories Chinese Academy of Sciences（中国科学院国家天文台光学天文重点实验室）；School of Computing Science Simon Fraser University（西蒙弗雷泽大学计算机科学学院）；College of Science Tibet University（西藏大学理学院）；Institute for Frontiers in Astronomy and Astrophysics Beijing Normal University（北京师范大学前沿天文与天体物理研究院）；Liii Network Co（Liii网络公司）
$\texttt{BTSbot}$: A Multi-input Convolutional Neural Network to Automate and Expedite Bright Transient Identification for the Zwicky Transient Facility
The Photometric LSST Astronomical Time-series Classification Challenge (PLAsTiCC): Selection of a performance metric for classification probabilities balancing diverse science goals
