92 citations · 612 across the 42 of their papers we have counts for
49 papers
Open Problems in (Hyper)Graph Decomposition
Deepak Ajwani, Rob H. Bisseling, Katrin Casel +26
Large networks are useful in a wide range of applications. Sometimes problem instances are composed of billions of entities. Decomposing and analyzing these structures helps us gai…
Hybrid Quantum-Classical Multilevel Approach for Maximum Cuts on Graphs
Anthony Angone, Xioayuan Liu, Ruslan Shaydulin +1
Combinatorial optimization is one of the fields where near term quantum devices are being utilized with hybrid quantum-classical algorithms to demonstrate potentially practical app…
Symmetries and Dimension Reduction in Quantum Approximate Optimization Algorithm
Boris Tsvelikhovskiy, Ilya Safro, Yuri Alexeev
In this paper, the Quantum Approximate Optimization Algorithm (QAOA) is analyzed by leveraging symmetries inherent in problem Hamiltonians. We focus on the generalized formulation…
Classical symmetries and the Quantum Approximate Optimization Algorithm
Ruslan Shaydulin, Stuart Hadfield, Tad Hogg +1
We study the relationship between the Quantum Approximate Optimization Algorithm (QAOA) and the underlying symmetries of the objective function to be optimized. Our approach formal…
Recent Advances in Scalable Network Generation
Manuel Penschuck, Ulrik Brandes, Michael Hamann +5
Random graph models are frequently used as a controllable and versatile data source for experimental campaigns in various research fields. Generating such data-sets at scale is a n…
Unsupervised Hierarchical Graph Representation Learning by Mutual Information Maximization
Fei Ding, Xiaohong Zhang, Justin Sybrandt +1
Graph representation learning based on graph neural networks (GNNs) can greatly improve the performance of downstream tasks, such as node and graph classification. However, the gen…