3 papers
quant-ph2026
Sparsified Kolmogorov-Arnold Networks for Interpretable Quantum State Tomography
Xinge Wu, Huaxin Wang, Jiajun Liu +4
Machine-learning approaches to quantum state tomography can achieve high reconstruction fidelity, but the physical structure used by the trained model often remains implicit. Here…
quant-ph2026
Scalable Quantum Error Mitigation with Physically Informed Graph Neural Networks
Huaxin Wang, Xinge Wu, Jiajun Liu +4
Quantum error mitigation (QEM) provides a practical route for estimating reliable observables on noisy intermediate-scale quantum (NISQ) devices. Traditional QEM strategies, includ…
cs.LG2023
AutoTransfer: AutoML with Knowledge Transfer -- An Application to Graph Neural Networks
Kaidi Cao, Jiaxuan You, Jiaju Liu +1
AutoML has demonstrated remarkable success in finding an effective neural architecture for a given machine learning task defined by a specific dataset and an evaluation metric. How…