Abstract: A method for quantum-assisted machine learning includes encoding, by processing circuitry, classical data into a plurality of quantum states by applying the classical data to an encoding map, and training a quantum model based on the plurality of quantum states. The quantum model may have a tensor network structure. The method may also include compiling, by the processing circuitry, the quantum model into a quantum circuit by mapping virtual qubits onto hardware qubits of a quantum hardware device, the quantum circuit including a sequence of operations tailored for operation on the quantum hardware device.