Supervised LDA restructuring of PCA-compressed embeddings raises silhouette separability from near zero to 0.197 in plant phenomics but yields mixed classical ML gains and persistent challenges for quantum kernel alignment under limited compute.
Barren plateaus in quantum neural network training landscapes.Nature communications, 9(1):4812
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Supervised Latent Restructuring for Small-Data Quantum Learning in Plant Phenomics
Supervised LDA restructuring of PCA-compressed embeddings raises silhouette separability from near zero to 0.197 in plant phenomics but yields mixed classical ML gains and persistent challenges for quantum kernel alignment under limited compute.