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Interview with prof. Tommaso Calarco from the Research Center J\"ulich (Germany) on Quantum Technologies and AI.
Comment: 5 pages, 1 photo, Will be published in the Journal K\"unstliche Intelligenz, Vol.4, 2024, Springer
Comment: 5 pages, 1 photo, Will be published in the Journal K\"unstliche Intelligenz, Vol.4, 2024, Springer
Externí odkaz:
http://arxiv.org/abs/2408.16014
Quantum Artificial Intelligence (QAI) is the intersection of quantum computing and AI, a technological synergy with expected significant benefits for both. In this paper, we provide a brief overview of what has been achieved in QAI so far and point t
Externí odkaz:
http://arxiv.org/abs/2408.10726
Autor:
Venkatesh, Supreeth Mysore, Macaluso, Antonio, Nuske, Marlon, Klusch, Matthias, Dengel, Andreas
The increasing number of Low Earth Orbit (LEO) satellites, driven by lower manufacturing and launch costs, is proving invaluable for Earth observation missions and low-latency internet connectivity. However, as the number of satellites increases, the
Externí odkaz:
http://arxiv.org/abs/2408.06007
Autor:
Venkatesh, Supreeth Mysore, Macaluso, Antonio, Nuske, Marlon, Klusch, Matthias, Dengel, Andreas
Quantum computing is expected to transform a range of computational tasks beyond the reach of classical algorithms. In this work, we examine the application of variational quantum algorithms (VQAs) for unsupervised image segmentation to partition ima
Externí odkaz:
http://arxiv.org/abs/2405.14405
Autor:
Venkatesh, Supreeth Mysore, Macaluso, Antonio, Nuske, Marlon, Klusch, Matthias, Dengel, Andreas
We present Q-Seg, a novel unsupervised image segmentation method based on quantum annealing, tailored for existing quantum hardware. We formulate the pixel-wise segmentation problem, which assimilates spectral and spatial information of the image, as
Externí odkaz:
http://arxiv.org/abs/2311.12912
The task of collision-free navigation (CFN) of self-driving cars is an NP-hard problem usually tackled using Deep Reinforcement Learning (DRL). While DRL methods have proven to be effective, their implementation requires substantial computing resourc
Externí odkaz:
http://arxiv.org/abs/2311.12875
Coalition Structure Generation (CSG) is an NP-Hard problem in which agents are partitioned into mutually exclusive groups to maximize their social welfare. In this work, we propose QuACS, a novel hybrid quantum classical algorithm for Coalition Struc
Externí odkaz:
http://arxiv.org/abs/2304.07218
Quantum Machine Learning has the potential to improve traditional machine learning methods and overcome some of the main limitations imposed by the classical computing paradigm. However, the practical advantages of using quantum resources to solve pa
Externí odkaz:
http://arxiv.org/abs/2303.11028
Autor:
Gupta, Dikshant, Klusch, Mathias
We present a novel hybrid learning method, HyLEAR, for solving the collision-free navigation problem for self-driving cars in POMDPs. HyLEAR leverages interposed learning to embed knowledge of a hybrid planner into a deep reinforcement learner to fas
Externí odkaz:
http://arxiv.org/abs/2301.00650
The problem of generating an optimal coalition structure for a given coalition game of rational agents is to find a partition that maximizes their social welfare and is known to be NP-hard. This paper proposes GCS-Q, a novel quantum-supported solutio
Externí odkaz:
http://arxiv.org/abs/2212.11372