Xinling Yu

According to our database, Xinling Yu authored at least 9 papers between 2022 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Photonic KAN: a Kolmogorov-Arnold network inspired efficient photonic neuromorphic architecture.

Yiwei Peng, Sean Hooten, Xinling Yu, Thomas Van Vaerenbergh, Yuan Yuan, Xian Xiao, Bassem Tossoun, Stanley Cheung, Marco Fiorentino, Raymond G. Beausoleil

CoRR, 2024

Separable Operator Networks.

Xinling Yu, Sean Hooten, Ziyue Liu, Yequan Zhao, Marco Fiorentino, Thomas Van Vaerenbergh, Zheng Zhang

CoRR, 2024

Real-Time FJ/MAC PDE Solvers via Tensorized, Back-Propagation-Free Optical PINN Training.

Yequan Zhao, Xian Xiao, Xinling Yu, Ziyue Liu, Zhixiong Chen, Geza Kurczveil, Raymond G. Beausoleil, Zheng Zhang

CoRR, 2024

2023

Tensor-Compressed Back-Propagation-Free Training for (Physics-Informed) Neural Networks.

Yequan Zhao, Xinling Yu, Zhixiong Chen, Ziyue Liu, Sijia Liu, Zheng Zhang

CoRR, 2023

PIFON-EPT: MR-Based Electrical Property Tomography Using Physics-Informed Fourier Networks.

Xinling Yu, José Enrique Cruz Serrallés, Ilias I. Giannakopoulos, Ziyue Liu, Luca Daniel, Riccardo Lattanzi, Zheng Zhang

CoRR, 2023

DeepOHeat: Operator Learning-based Ultra-fast Thermal Simulation in 3D-IC Design.

Ziyue Liu, Yixing Li, Jing Hu, Xinling Yu, Shinyu Shiau, Xin Ai, Zhiyu Zeng, Zheng Zhang

Proceedings of the 60th ACM/IEEE Design Automation Conference, 2023

2022

When and why PINNs fail to train: A neural tangent kernel perspective.

Sifan Wang, Xinling Yu, Paris Perdikaris

J. Comput. Phys., 2022

MR-Based Electrical Property Reconstruction Using Physics-Informed Neural Networks.

Xinling Yu, José Enrique Cruz Serrallés, Ilias I. Giannakopoulos, Ziyue Liu, Luca Daniel, Riccardo Lattanzi, Zheng Zhang

CoRR, 2022

TT-PINN: A Tensor-Compressed Neural PDE Solver for Edge Computing.

Ziyue Liu, Xinling Yu, Zheng Zhang

CoRR, 2022