9 citations · 29 across the 9 of their papers we have counts for
4 papers · 1 filter
SHoP: A Deep Learning Framework for Solving High-order Partial Differential Equations
Tingxiong Xiao, Runzhao Yang, Yuxiao Cheng +2
Solving partial differential equations (PDEs) has been a fundamental problem in computational science and of wide applications for both scientific and engineering research. Due to…
CUTS+: High-dimensional Causal Discovery from Irregular Time-series
Yuxiao Cheng, Lianglong Li, Tingxiong Xiao +4
Causal discovery in time-series is a fundamental problem in the machine learning community, enabling causal reasoning and decision-making in complex scenarios. Recently, researcher…
CUTS: Neural Causal Discovery from Irregular Time-Series Data
Yuxiao Cheng, Runzhao Yang, Tingxiong Xiao +4
Causal discovery from time-series data has been a central task in machine learning. Recently, Granger causality inference is gaining momentum due to its good explainability and hig…
Optical Neural Ordinary Differential Equations
Yun Zhao, Hang Chen, Min Lin +5
Increasing the layer number of on-chip photonic neural networks (PNNs) is essential to improve its model performance. However, the successively cascading of network hidden layers r…