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Katzgraber, Helmut G.
318
results:
Search for persons
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Format
Online (315)
Print (3)
Mediatypes
Articles (Online) (123)
Articles (Print) (3)
Bookchapter (Online) (3)
OpenAccess-fulltext (189)
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english (147)
german (1)
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1
Designing quantum annealing schedules using Bayesian optimi..:
Finžgar, Jernej Rudi
;
Schuetz, Martin J. A.
;
Brubaker, J. Kyle
..
Physical Review Research. 6 (2024) 2 - p. , 2024
Link:
https://doi.org/10.1103/..
?
2
Quantum-Informed Recursive Optimization Algorithms:
Finžgar, Jernej Rudi
;
Kerschbaumer, Aron
;
Schuetz, Martin J.A.
..
PRX Quantum. 5 (2024) 2 - p. , 2024
Link:
https://doi.org/10.1103/..
?
3
Hardness of the maximum-independent-set problem on unit-dis..:
Andrist, Ruben S.
;
Schuetz, Martin J. A.
;
Minssen, Pierre
...
Physical Review Research. 5 (2023) 4 - p. , 2023
Link:
https://doi.org/10.1103/..
?
4
End-To-End Resource Analysis for Quantum Interior-Point Met..:
Dalzell, Alexander M.
;
Clader, B. David
;
Salton, Grant
...
PRX Quantum. 4 (2023) 4 - p. , 2023
Link:
https://doi.org/10.1103/..
?
5
Explainable Artificial Intelligence Using Expressive Boolea..:
Rosenberg, Gili
;
Brubaker, John Kyle
;
Schuetz, Martin J. A.
...
Machine Learning and Knowledge Extraction. 5 (2023) 4 - p. 1760-1795 , 2023
Link:
https://doi.org/10.3390/..
?
6
Combinatorial optimization with physics-inspired graph neur..:
Schuetz, Martin J. A.
;
Brubaker, J. Kyle
;
Katzgraber, Helmut G.
Nature Machine Intelligence. 4 (2022) 4 - p. 367-377 , 2022
Link:
https://doi.org/10.1038/..
?
7
Reply to: Inability of a graph neural network heuristic to ..:
Schuetz, Martin J. A.
;
Brubaker, J. Kyle
;
Katzgraber, Helmut G.
Nature Machine Intelligence. 5 (2022) 1 - p. 26-28 , 2022
Link:
https://doi.org/10.1038/..
?
8
Graph coloring with physics-inspired graph neural networks:
Schuetz, Martin J. A.
;
Brubaker, J. Kyle
;
Zhu, Zhihuai
.
Physical Review Research. 4 (2022) 4 - p. , 2022
Link:
https://doi.org/10.1103/..
?
9
Optimization of Robot-Trajectory Planning with Nature-Inspi..:
Schuetz, Martin J.A.
;
Brubaker, J. Kyle
;
Montagu, Henry
...
Physical Review Applied. 18 (2022) 5 - p. , 2022
Link:
https://doi.org/10.1103/..
?
10
Reply to: Modern graph neural networks do worse than classi..:
Schuetz, Martin J. A.
;
Brubaker, J. Kyle
;
Katzgraber, Helmut G.
Nature Machine Intelligence. 5 (2022) 1 - p. 32-34 , 2022
Link:
https://doi.org/10.1038/..
?
11
Computational overhead of locality reduction in binary opti..:
Valiante, Elisabetta
;
Hernandez, Maritza
;
Barzegar, Amin
.
Computer Physics Communications. 269 (2021) - p. 108102 , 2021
Link:
https://doi.org/10.1016/..
?
12
Automated design of pulse sequences for magnetic resonance ..:
Jordan, Stephen P.
;
Hu, Siyuan
;
Rozada, Ignacio
...
Proceedings of the National Academy of Sciences. 118 (2021) 40 - p. , 2021
Link:
https://doi.org/10.1073/..
?
13
Optimization and benchmarking of the thermal cycling algori..:
Barzegar, Amin
;
Kankani, Anuj
;
Mandrà, Salvatore
.
Physical Review E. 104 (2021) 3 - p. , 2021
Link:
https://doi.org/10.1103/..
?
14
Embedding Overhead Scaling of Optimization Problems in Quan..:
Könz, Mario S.
;
Lechner, Wolfgang
;
Katzgraber, Helmut G.
.
PRX Quantum. 2 (2021) 4 - p. , 2021
Link:
https://doi.org/10.1103/..
?
15
Machine learning in physics: the pitfalls of poisoned train..:
Fang, Chao
;
Barzeger, Amin
;
Katzgraber, Helmut G
Machine Learning: Science and Technology. 1 (2020) 4 - p. 045001 , 2020
Link:
https://doi.org/10.1088/..
1-15