MCTS discovers superior data encoding circuits for QCCNNs that outperform standard encodings on medical datasets, with effective rank of feature maps serving as a performance predictor.
Medmnist v2-a large-scale lightweight benchmark for 2d and 3d biomedical image classifica- tion
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Discovering Data Encoding Strategies for Quantum-Classical Neural Networks Using Monte Carlo Tree Search
MCTS discovers superior data encoding circuits for QCCNNs that outperform standard encodings on medical datasets, with effective rank of feature maps serving as a performance predictor.