Automatic Machine Learning Framework to Study Morphological Parameters of AGN Host Galaxies within $z < 1.4$ in the Hyper Supreme-Cam Wide Survey

28 January 2025

Papers citing "Automatic Machine Learning Framework to Study Morphological Parameters of AGN Host Galaxies within $z < 1.4$ in the Hyper Supreme-Cam Wide Survey"

6 / 6 papers shown

Title
Using Machine Learning to Determine Morphologies of $z<1$ AGN Host Galaxies in the Hyper Suprime-Cam Wide Survey Chuan Tian C. Urry Aritra Ghosh Ryan Ofman T. Ananna ... M. Powell D. Sanders Kevin Schawinski Dominic Stark G. Tremblay AI4CE 30 3 0 20 Dec 2022
Array Programming with NumPy Charles R. Harris K. Millman S. Walt R. Gommers Pauli Virtanen ... Tyler Reddy Warren Weckesser Hameer Abbasi C. Gohlke T. Oliphant 205 15,182 0 18 Jun 2020
Morpheus: A Deep Learning Framework For Pixel-Level Analysis of Astronomical Image Data R. Hausen B. Robertson 67 68 0 26 Jun 2019
Galaxy Zoo: Probabilistic Morphology through Bayesian CNNs and Active Learning Mike Walmsley Lewis Smith Chris J. Lintott Y. Gal S. Bamford ... K. Masters C. Scarlata B. Simmons R. Smethurst D. Wright 77 89 0 17 May 2019
Using transfer learning to detect galaxy mergers Sandro Ackermann Kevin Schawinski Ce Zhang Anna K. Weigel M. D. Turp 3DPC 56 111 0 25 May 2018
Rotation-invariant convolutional neural networks for galaxy morphology prediction Sander Dieleman K. Willett J. Dambre 113 655 0 24 Mar 2015