4 papers
Practical Noise Mitigation for Quantum Annealing via Dynamical Decoupling: Toward Industry-Relevant Optimization using Trapped Ions
Sebastian Nagies, Chiara Capecci, Marcel Seelbach Benkner +6
Quantum annealing is a framework for solving combinatorial optimization problems. While it offers a promising path towards a practical application of quantum hardware, its performa…
Quantum-enhanced Computer Vision: Going Beyond Classical Algorithms
Natacha Kuete Meli, Shuteng Wang, Marcel Seelbach Benkner +5
Quantum-enhanced Computer Vision (QeCV) is a new research field at the intersection of computer vision, optimisation theory, machine learning and quantum computing. It has high pot…
ONNX-Net: Towards Universal Representations and Instant Performance Prediction for Neural Architectures
Shiwen Qin, Alexander Auras, Shay B. Cohen +4
Neural architecture search (NAS) automates the design process of high-performing architectures, but remains bottlenecked by expensive performance evaluation. Most existing studies…
Compensating connectivity restrictions in quantum annealers via splitting and linearization techniques
Marcel Seelbach Benkner, Zorah Lähner, Vladislav Golyanik +2
Current quantum annealing experiments often suffer from restrictions in connectivity in the sense that only certain qubits can be coupled to each other. The most common strategy to…