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Found 5 papers, 4 papers with code
Q-Seg: Quantum Annealing-based Unsupervised Image Segmentation
Thus, Q-Seg emerges as a viable alternative for real-world applications using available quantum hardware, particularly in scenarios where the lack of labeled data and computational runtime are critical.
Nav-Q: Quantum Deep Reinforcement Learning for Collision-Free Navigation of Self-Driving Cars
In this work, we propose Nav-Q, the first quantum-supported DRL algorithm for CFN of self-driving cars, that leverages quantum computation for improving the training performance without the requirement for onboard quantum hardware.
MAQA: A Quantum Framework for Supervised Learning
In its general formulation, MAQA can be potentially adopted as the quantum counterpart of all those models falling into the scheme of aggregation of multiple functions, such as ensemble algorithms and neural networks.
GCS-Q: Quantum Graph Coalition Structure Generation
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.
BILP-Q: Quantum Coalition Structure Generation
Quantum AI is an emerging field that uses quantum computing to solve typical complex problems in AI.
