most citedFunctional PCA and Deep Neural Networks-based Bayesian Inverse Uncertainty Quantification with Transient Experimental Data

20 citations · 37 across the 3 of their papers we have counts for

collaborators

3 papers

cs.LG2023★ 16 cited

Fast and Accurate Reduced-Order Modeling of a MOOSE-based Additive Manufacturing Model with Operator Learning

Mahmoud Yaseen, Dewen Yushu, Peter German +1

One predominant challenge in additive manufacturing (AM) is to achieve specific material properties by manipulating manufacturing process parameters during the runtime. Such manipu…

stat.ML2023★ 20 cited

Functional PCA and Deep Neural Networks-based Bayesian Inverse Uncertainty Quantification with Transient Experimental Data

Ziyu Xie, Mahmoud Yaseen, Xu Wu

Inverse UQ is the process to inversely quantify the model input uncertainties based on experimental data. This work focuses on developing an inverse UQ process for time-dependent r…

cs.LG2019★ 1 cited

Layer Pruning for Accelerating Very Deep Neural Networks

Weiwei Zhang, Changsheng chen, Xuechun Wu +4

In this paper, we propose an adaptive pruning method. This method can cut off the channel and layer adaptively. The proportion of the layer and the channel to be cut is learned ada…