Open Access Helper

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:

A simple linear algebra identity to optimize large-scale neural network quantum states
Riccardo Rende, Luciano Loris Viteritti, Lorenzo Bardone, et al.
Communications Physics (2024) Vol. 7, Iss. 1
Open Access | Times Cited: 20

Showing 20 citing articles:

Empowering deep neural quantum states through efficient optimization
Ao Chen, Markus Heyl
Nature Physics (2024) Vol. 20, Iss. 9, pp. 1476-1481
Open Access | Times Cited: 20
Beyond-classical computation in quantum simulation
Andrew King, Alberto Nocera, Marek M. Rams, et al.
Science (2025)
Closed Access | Times Cited: 3
Transformer neural networks and quantum simulators: a hybrid approach for simulating strongly correlated systems
Hannah Lange, Guillaume Bornet, Gabriel Emperauger, et al.
Quantum (2025) Vol. 9, pp. 1675-1675
Open Access | Times Cited: 1
Efficient optimization of variational autoregressive networks with natural gradient
Jing Liu, Ying Tang, Pan Zhang
Physical review. E (2025) Vol. 111, Iss. 2
Closed Access | Times Cited: 1
From Architectures to Applications: A Review of Neural Quantum States
Hannah Lange, Anka Van de Walle, Atiye Abedinnia, et al.
Quantum Science and Technology (2024) Vol. 9, Iss. 4, pp. 040501-040501
Open Access | Times Cited: 6
Low-Light Liquid Content Detection in Transparent Containers: A Benchmark
Jiwei Mo, Y. H. Tan, Ling Huang, et al.
(2025)
Closed Access
Autoregressive neural quantum states of Fermi Hubbard models
Eduardo Ibarra-García-Padilla, Hannah Lange, Roger G. Melko, et al.
Physical Review Research (2025) Vol. 7, Iss. 1
Open Access
Phase diagram of the J1−J2 Heisenberg second-order topological quantum magnet
Pascal M. Vecsei, José L. Lado
Physical Review Research (2025) Vol. 7, Iss. 1
Open Access
Paths towards time evolution with larger neural-network quantum states
Wenxuan Zhang, Bo Xing, Xiansong Xu, et al.
Computer Physics Communications (2025), pp. 109577-109577
Closed Access
Neural quantum state study of fracton models
Marc Machaczek, Lode Pollet, Ke Liu
SciPost Physics (2025) Vol. 18, Iss. 3
Open Access
Transformer wave function for two dimensional frustrated magnets: Emergence of a spin-liquid phase in the Shastry-Sutherland model
Luciano Loris Viteritti, Riccardo Rende, Alberto Parola, et al.
Physical review. B./Physical review. B (2025) Vol. 111, Iss. 13
Open Access
Simple Fermionic backflow states via a systematically improvable tensor decomposition
Massimo Bortone, Yannic Rath, George H. Booth
Communications Physics (2025) Vol. 8, Iss. 1
Open Access
Second-order optimization strategies for neural network quantum states
M. Drissi, J. W. T. Keeble, J. Rozalén Sarmiento, et al.
Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences (2024) Vol. 382, Iss. 2275
Closed Access | Times Cited: 3
Fine-tuning neural network quantum states
Riccardo Rende, Sebastian Goldt, Federico Becca, et al.
Physical Review Research (2024) Vol. 6, Iss. 4
Open Access | Times Cited: 2
What does self-attention learn from Masked Language Modelling?
Riccardo Rende, Federica Gerace, Alessandro Laio, et al.
arXiv (Cornell University) (2023)
Open Access | Times Cited: 4
Quantum skyrmion dynamics studied by neural network quantum states
Ashish Joshi, Robert Peters, Thore Posske
Physical review. B./Physical review. B (2024) Vol. 110, Iss. 10
Open Access | Times Cited: 1
Are queries and keys always relevant? A case study on Transformer wave functions
Riccardo Rende, Luciano Loris Viteritti
Machine Learning Science and Technology (2024) Vol. 6, Iss. 1, pp. 010501-010501
Open Access | Times Cited: 1
Phase diagram of the $J$-$J_d$ Heisenberg Model on the Maple-Leaf Lattice: Neural networks and density matrix renormalization group
Jonas Beck, Jonathan Bodky, Johannes Motruk, et al.
arXiv (Cornell University) (2024)
Open Access
A Kaczmarz-inspired approach to accelerate the optimization of neural network wavefunctions
Gil Goldshlager, Nilin Abrahamsen, Lin Lin
arXiv (Cornell University) (2024)
Open Access
Deep learning lattice gauge theories
Anuj Apte, Clay Córdova, Tzu-Chen Huang, et al.
Physical review. B./Physical review. B (2024) Vol. 110, Iss. 16
Open Access
Quantum Many-Body Solver Using Artificial Neural Networks and its Applications to Strongly Correlated Electron Systems
Yusuke Nomura, Masatoshi Imada
Journal of the Physical Society of Japan (2024) Vol. 94, Iss. 3
Open Access
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