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This paper introduces Quiver, a paradigm that enriches classical machine learning models with quantum-inspired features derived from the quantum Fisher information matrix, demonstrating improvements on molecule property prediction and jet flavor classification benchmarks.
This paper presents empirical evidence that quantum entanglement provides a measurable advantage in multi-agent reinforcement learning, using the CHSH game and cooperative navigation tasks to demonstrate performance improvements over classical baselines.