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Katzgraber, Helmut G.
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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/..
 
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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/..
 
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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/..
 
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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/..
 
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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/..
 
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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/..
 
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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/..
 
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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/..
 
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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/..
 
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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/..
 
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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/..
 
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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/..
 
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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/..
 
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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/..
 
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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/..
 
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