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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

The Dawes Review 10: The impact of deep learning for the analysis of galaxy surveys
Marc Huertas-Company, François Lanusse
Publications of the Astronomical Society of Australia (2023) Vol. 40
Open Access | Times Cited: 58

Showing 26-50 of 58 citing articles:

Fast and efficient identification of anomalous galaxy spectra with neural density estimation
Vanessa Böhm, Alex Kim, S. Juneau
Monthly Notices of the Royal Astronomical Society (2023) Vol. 526, Iss. 2, pp. 3072-3087
Open Access | Times Cited: 6
YOLO–CL: Galaxy cluster detection in the SDSS with deep machine learning
Kirill Grishin, S. Mei, S. Ilić
Astronomy and Astrophysics (2023) Vol. 677, pp. A101-A101
Open Access | Times Cited: 5
Morphological classification of radio galaxies with Wasserstein generative adversarial network-supported augmentation
L. Rustige, Janis Kummer, Florian Griese, et al.
RAS Techniques and Instruments (2023) Vol. 2, Iss. 1, pp. 264-277
Open Access | Times Cited: 5
Ask the machine: systematic detection of wind-type outflows in low-mass X-ray binaries
D. Mata Sánchez, T. Muñoz‐Darias, J. Casares, et al.
Monthly Notices of the Royal Astronomical Society (2023) Vol. 524, Iss. 1, pp. 338-350
Open Access | Times Cited: 5
A morphological segmentation approach to determining bar lengths
Mitchell K Cavanagh, Kenji Bekki, Brent Groves
Monthly Notices of the Royal Astronomical Society (2024) Vol. 530, Iss. 1, pp. 1171-1194
Open Access | Times Cited: 1
Katachi (形): Decoding the Imprints of Past Star Formation on Present-day Morphology in Galaxies with Interpretable CNNs*
Juan Pablo Alfonzo, Kartheik G. Iyer, Masayuki Akiyama, et al.
The Astrophysical Journal (2024) Vol. 967, Iss. 2, pp. 152-152
Open Access | Times Cited: 1
Applying machine learning to Galactic Archaeology: how well can we recover the origin of stars in Milky Way-like galaxies?
Andrea Sante, Andreea S. Font, Sandra Ortega‐Martorell, et al.
Monthly Notices of the Royal Astronomical Society (2024) Vol. 531, Iss. 4, pp. 4363-4382
Open Access | Times Cited: 1
Bayesian and convolutional networks for hierarchical morphological classification of galaxies
Jonathan Serrano-Pérez, R. Díaz Hernández, L. Enrique Sucar
Experimental Astronomy (2024) Vol. 58, Iss. 2
Closed Access | Times Cited: 1
A post-merger enhancement only in star-forming Type 2 Seyfert galaxies: the deep learning view
Mathilda Avirett-Mackenzie, C. Villforth, Marc Huertas-Company, et al.
Monthly Notices of the Royal Astronomical Society (2024) Vol. 528, Iss. 4, pp. 6915-6933
Open Access | Times Cited: 1
A versatile framework for analyzing galaxy image data by incorporating Human-in-the-loop in a large vision model*
Mingxiang Fu, Yu Song, Jiameng Lv, et al.
Chinese Physics C (2024) Vol. 48, Iss. 9, pp. 095001-095001
Closed Access | Times Cited: 1
Deep Learning Voigt Profiles. I. Single-Cloud Doublets
Bryson Stemock, Christopher W. Churchill, Avery Lee, et al.
The Astronomical Journal (2024) Vol. 167, Iss. 6, pp. 287-287
Open Access | Times Cited: 1
What drives the variance of galaxy spectra?
Zahra Sharbaf, Ignacio Ferreras, O. Lahav
Monthly Notices of the Royal Astronomical Society (2023) Vol. 526, Iss. 1, pp. 585-599
Open Access | Times Cited: 3
AstroCLIP: Cross-Modal Pre-Training for Astronomical Foundation Models
François Lanusse, Liam Parker, Siavash Golkar, et al.
arXiv (Cornell University) (2023)
Open Access | Times Cited: 3
Predictive uncertainty on astrophysics recovery from multifield cosmology
Sambatra Andrianomena, Sultan Hassan
Journal of Cosmology and Astroparticle Physics (2023) Vol. 2023, Iss. 06, pp. 051-051
Open Access | Times Cited: 2
Uncertainty quantification of the virial black hole mass with conformal prediction
Suk Yee Yong, Cheng Soon Ong
Monthly Notices of the Royal Astronomical Society (2023) Vol. 524, Iss. 2, pp. 3116-3129
Open Access | Times Cited: 2
Accelerating galaxy dynamical modeling using a neural network for joint lensing and kinematic analyses
Matthew R. Gomer, Sebastian Ertl, Luca Biggio, et al.
Astronomy and Astrophysics (2023) Vol. 679, pp. A59-A59
Open Access | Times Cited: 2
Reconstructing Lyα Fields from Low-resolution Hydrodynamical Simulations with Deep Learning
Cooper Jacobus, Peter Harrington, Zarija Lukić
The Astrophysical Journal (2023) Vol. 958, Iss. 1, pp. 21-21
Open Access | Times Cited: 2
Deep learning cosmic ray transport from density maps of simulated, turbulent gas
Chad Bustard, John F. Wu
Machine Learning Science and Technology (2024) Vol. 5, Iss. 1, pp. 015028-015028
Open Access
Generating galaxy clusters mass density maps from mock multiview images via deep learning
Daniel de Andrés, Weiguang Cui, Gustavo Yepes, et al.
EPJ Web of Conferences (2024) Vol. 293, pp. 00013-00013
Open Access
Vector to Matrix Representation for Cnn Networks for Classifying Astronomical Data
Loris Nanni, Sheryl Brahnam
(2024)
Closed Access
Exploring galaxy properties of eCALIFA with contrastive learning
G. Martínez-Solaeche, R. García-Benito, R. M. González Delgado, et al.
Astronomy and Astrophysics (2024) Vol. 688, pp. A160-A160
Open Access
Datacube segmentation via Deep Spectral Clustering
Alessandro Bombini, Fernando Garcı́a-Avello Bofı́as, Caterina Bracci, et al.
Machine Learning Science and Technology (2024) Vol. 5, Iss. 3, pp. 035024-035024
Open Access
Estimation of line-of-sight velocities of individual galaxies using neural networks – I. Modelling redshift–space distortions at large scales
Hongxiang Chen, Jie Wang, Tianxiang Mao, et al.
Monthly Notices of the Royal Astronomical Society (2024) Vol. 532, Iss. 4, pp. 3947-3960
Open Access
Vector to matrix representation for CNN networks for classifying astronomical data
Loris Nanni, Sheryl Brahnam
Astronomy and Computing (2024) Vol. 49, pp. 100864-100864
Open Access
The Application of Manifold Learning to a Selection of Different Galaxy Populations and Scaling Relation Analysis
Sogol Sanjaripour, Shoubaneh Hemmati, Bahram Mobasher, et al.
The Astrophysical Journal (2024) Vol. 977, Iss. 2, pp. 202-202
Open Access

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