3 citations · 14 across the 45 of their papers we have counts for
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Reducing QUBO Density by Factoring Out Semi-Symmetries
Jonas Nüßlein, Leo Sünkel, Jonas Stein +6
Quantum Approximate Optimization Algorithm (QAOA) and Quantum Annealing are prominent approaches for solving combinatorial optimization problems, such as those formulated as Quadra…
Coconut Palm Tree Counting on Drone Images with Deep Object Detection and Synthetic Training Data
Tobias Rohe, Barbara Böhm, Michael Kölle +3
Drones have revolutionized various domains, including agriculture. Recent advances in deep learning have propelled among other things object detection in computer vision. This stud…
Optimizing Sensor Redundancy in Sequential Decision-Making Problems
Jonas Nüßlein, Maximilian Zorn, Fabian Ritz +5
Reinforcement Learning (RL) policies are designed to predict actions based on current observations to maximize cumulative future rewards. In real-world applications (i.e., non-simu…
Reducing QAOA Circuit Depth by Factoring out Semi-Symmetries
Jonas Nüßlein, Leo Sünkel, Jonas Stein +4
QAOA is a quantum algorithm for solving combinatorial optimization problems. It is capable of searching for the minimizing solution vector of a QUBO problem . The number…
Learning State-Dependent Policy Parametrizations for Dynamic Technician Routing with Rework
Jonas Stein, Florentin D Hildebrandt, Barrett W Thomas +1
Home repair and installation services require technicians to visit customers and resolve tasks of different complexity. Technicians often have heterogeneous skills and working expe…
Sequential Hamiltonian Assembly: Enhancing the training of combinatorial optimization problems on quantum computers
Navid Roshani, Jonas Stein, Maximilian Zorn +3
A central challenge in quantum machine learning is the design and training of parameterized quantum circuits (PQCs). Much like in deep learning, vanishing gradients pose significan…