7 citations · 12 across the 4 of their papers we have counts for
4 papers
Topological Analysis of Mouse Brain Vasculature via 3D Light-sheet Microscopy Images
Jiachen Yao, Nina Hagemann, Qiaojie Xiong +3
Vascular networks play a crucial role in understanding brain functionalities. Brain integrity and function, neuronal activity and plasticity, which are crucial for learning, are ac…
Preconditioning for Physics-Informed Neural Networks
Songming Liu, Chang Su, Jiachen Yao +4
Physics-informed neural networks (PINNs) have shown promise in solving various partial differential equations (PDEs). However, training pathologies have negatively affected the con…
Learning to Segment from Noisy Annotations: A Spatial Correction Approach
Jiachen Yao, Yikai Zhang, Songzhu Zheng +3
Noisy labels can significantly affect the performance of deep neural networks (DNNs). In medical image segmentation tasks, annotations are error-prone due to the high demand in ann…
MultiAdam: Parameter-wise Scale-invariant Optimizer for Multiscale Training of Physics-informed Neural Networks
Jiachen Yao, Chang Su, Zhongkai Hao +3
Physics-informed Neural Networks (PINNs) have recently achieved remarkable progress in solving Partial Differential Equations (PDEs) in various fields by minimizing a weighted sum…