Tai-Yue Li

HQKAN achieves superior ECG classification performance while cutting down trainable parameters and communication costs by over 37%—a game changer for privacy-sensitive federated learning.

Coordinate-wise memory control through CMG enables unprecedented accuracy in forecasting quantum dynamics, outperforming traditional methods by over 91%.

G-QKANFWP outperforms traditional LSTMs in traffic forecasting while using a fraction of the resources, redefining efficiency in network control.