Quantum Incremental Learning with Mixed State Prototypes
This work introduces a novel quantum incremental learning framework based on trainable mixed-state prototypes that achieves high-dimensional feature concentration using a minimal number of qubits, while demonstrating lower computational complexity and robust representation in incremental learning tasks compared with cl...