John Kyle Brubaker

According to our database, John Kyle Brubaker authored at least 11 papers between 2022 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Optimization of Next-Day Delivery Coverage using Constraint Programming and Random Key Optimizers.

John Kyle Brubaker, Kyle E. C. Booth, Martin J. A. Schuetz, Philipp Loick, Jian Shen, Arun Ramamurthy, Georgios Paschos

CoRR, April, 2025

BoolXAI: Explainable AI Using Expressive Boolean Formulas.

Serdar Kadioglu, Elton Yechao Zhu, Gili Rosenberg, John Kyle Brubaker, Martin J. A. Schuetz, Grant Salton, Zhihuai Zhu, Helmut G. Katzgraber

Proceedings of the AAAI-25, Sponsored by the Association for the Advancement of Artificial Intelligence, February 25, 2025

2024

Scalable iterative pruning of large language and vision models using block coordinate descent.

Gili Rosenberg, John Kyle Brubaker, Martin J. A. Schuetz, Elton Yechao Zhu, Serdar Kadioglu, Sima E. Borujeni, Helmut G. Katzgraber

CoRR, 2024

A Random-Key Optimizer for Combinatorial Optimization.

Antonio A. Chaves, Mauricio G. C. Resende, Martin J. A. Schuetz, John Kyle Brubaker, Helmut G. Katzgraber, Edilson Fernandes de Arruda, Ricardo M. A. Silva

CoRR, 2024

2023

Explainable Artificial Intelligence Using Expressive Boolean Formulas.

Gili Rosenberg, John Kyle Brubaker, Martin J. A. Schuetz, Grant Salton, Zhihuai Zhu, Elton Yechao Zhu, Serdar Kadioglu, Sima E. Borujeni, Helmut G. Katzgraber

Mach. Learn. Knowl. Extr., December, 2023

Reply to: Modern graph neural networks do worse than classical greedy algorithms in solving combinatorial optimization problems like maximum independent set.

Martin J. A. Schuetz, John Kyle Brubaker, Helmut G. Katzgraber

Nat. Mac. Intell., January, 2023

Reply to: Inability of a graph neural network heuristic to outperform greedy algorithms in solving combinatorial optimization problems.

Martin J. A. Schuetz, John Kyle Brubaker, Helmut G. Katzgraber

Nat. Mac. Intell., January, 2023

Explainable AI using expressive Boolean formulas.

Gili Rosenberg, John Kyle Brubaker, Martin J. A. Schuetz, Grant Salton, Zhihuai Zhu, Elton Yechao Zhu, Serdar Kadioglu, Sima E. Borujeni, Helmut G. Katzgraber

CoRR, 2023

2022

Combinatorial optimization with physics-inspired graph neural networks.

Martin J. A. Schuetz, John Kyle Brubaker, Helmut G. Katzgraber

Nat. Mach. Intell., 2022

Optimization of Robot Trajectory Planning with Nature-Inspired and Hybrid Quantum Algorithms.

Martin J. A. Schuetz, John Kyle Brubaker, Henry Montagu, Yannick van Dijk, Johannes Klepsch, Philipp Ross, André Luckow, Mauricio G. C. Resende, Helmut G. Katzgraber

CoRR, 2022

Graph Coloring with Physics-Inspired Graph Neural Networks.

Martin J. A. Schuetz, John Kyle Brubaker, Zhihuai Zhu, Helmut G. Katzgraber

CoRR, 2022