OpenAlex Citation Counts

OpenAlex Citations Logo

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:

Anomalies, representations, and self-supervision
Barry M. Dillon, Luigi Favaro, Friedrich Feiden, et al.
SciPost Physics Core (2024) Vol. 7, Iss. 3
Open Access | Times Cited: 7

Showing 7 citing articles:

Masked Particle Modeling on Sets: Towards Self-Supervised High Energy Physics Foundation Models
T. Golling, L. Heinrich, M. Kagan, et al.
Machine Learning Science and Technology (2024) Vol. 5, Iss. 3, pp. 035074-035074
Open Access | Times Cited: 7

Semi-visible jets, energy-based models, and self-supervision
Luigi Favaro, Michael Krämer, Tanmoy Modak, et al.
SciPost Physics (2025) Vol. 18, Iss. 2
Open Access

Quantum similarity learning for anomaly detection
A. Hammad, Mihoko M. Nojiri, Masahito Yamazaki
Journal of High Energy Physics (2025) Vol. 2025, Iss. 2
Open Access

Method to simultaneously facilitate all jet physics tasks
V. M. Mikuni, Benjamin Nachman
Physical review. D/Physical review. D. (2025) Vol. 111, Iss. 5
Open Access

Solving key challenges in collider physics with foundation models
V. M. Mikuni, Benjamin Nachman
Physical review. D/Physical review. D. (2025) Vol. 111, Iss. 5
Open Access

Unsupervised and lightly supervised learning in particle physics
Jai Bardhan, Tanumoy Mandal, Subhadip Mitra, et al.
The European Physical Journal Special Topics (2024) Vol. 233, Iss. 15-16, pp. 2559-2596
Closed Access | Times Cited: 2

OmniJet-α: the first cross-task foundation model for particle physics
Joschka Birk, Anna Hallin, Gregor Kasieczka
Machine Learning Science and Technology (2024) Vol. 5, Iss. 3, pp. 035031-035031
Open Access | Times Cited: 1

Page 1

Scroll to top