178 citations · 256 across the 6 of their papers we have counts for
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quant-ph2021★ 11 cited
Performance analysis of a hybrid agent for quantum-accessible reinforcement learning
Arne Hamann, Sabine Wölk
In the last decade quantum machine learning has provided fascinating and fundamental improvements to supervised, unsupervised and reinforcement learning. In reinforcement learning,…
quant-ph2021★ 20 cited
Approximate decoherence free subspaces for distributed sensing
Arne Hamann, Pavel Sekatski, Wolfgang Dür
We consider the sensing of scalar valued fields with specific spatial dependence using a network of sensors, e.g. multiple atoms located at different positions within a trap. We sh…
quant-ph2021★ 178 cited
Experimental quantum speed-up in reinforcement learning agents
Valeria Saggio, Beate E. Asenbeck, Arne Hamann +10
Increasing demand for algorithms that can learn quickly and efficiently has led to a surge of development within the field of artificial intelligence (AI). An important paradigm wi…