178 citations · 256 across the 6 of their papers we have counts for
6 papers
Optimal distributed multiparameter estimation in noisy environments
Arne Hamann, Pavel Sekatski, Wolfgang Dür
We consider the task of multiple parameter estimation in the presence of strong correlated noise with a network of distributed sensors. We study how to find and improve noise-insen…
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,…
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…
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…
Quantum-accessible reinforcement learning beyond strictly epochal environments
A. Hamann, V. Dunjko, S. Wölk
In recent years, quantum-enhanced machine learning has emerged as a particularly fruitful application of quantum algorithms, covering aspects of supervised, unsupervised and reinfo…
Photonic architecture for reinforcement learning
Fulvio Flamini, Arne Hamann, Sofiène Jerbi +3
The last decade has seen an unprecedented growth in artificial intelligence and photonic technologies, both of which drive the limits of modern-day computing devices. In line with…