137 citations · 828 across the 29 of their papers we have counts for
4 papers · 1 filter
Quantum Policy Gradient Algorithm with Optimized Action Decoding
Nico Meyer, Daniel D. Scherer, Axel Plinge +2
Quantum machine learning implemented by variational quantum circuits (VQCs) is considered a promising concept for the noisy intermediate-scale quantum computing era. Focusing on ap…
A Survey on Quantum Reinforcement Learning
Nico Meyer, Christian Ufrecht, Maniraman Periyasamy +3
Quantum reinforcement learning is an emerging field at the intersection of quantum computing and machine learning. While we intend to provide a broad overview of the literature on…
Incremental Data-Uploading for Full-Quantum Classification
Maniraman Periyasamy, Nico Meyer, Christian Ufrecht +3
The data representation in a machine-learning model strongly influences its performance. This becomes even more important for quantum machine learning models implemented on noisy i…
Uncovering Instabilities in Variational-Quantum Deep Q-Networks
Maja Franz, Lucas Wolf, Maniraman Periyasamy +5
Deep Reinforcement Learning (RL) has considerably advanced over the past decade. At the same time, state-of-the-art RL algorithms require a large computational budget in terms of t…