17 citations · 17 across the 5 of their papers we have counts for
5 papers
An ILUES-based adaptive Gaussian process method for multimodal Bayesian inverse problems
Zhihang Xu, Xiaoyu Zhu, Daoji Li +1
Inverse problems are prevalent in both scientific research and engineering applications. In the context of Bayesian inverse problems, sampling from the posterior distribution can b…
A domain-decomposed VAE method for Bayesian inverse problems
Zhihang Xu, Yingzhi Xia, Qifeng Liao
Bayesian inverse problems are often computationally challenging when the forward model is governed by complex partial differential equations (PDEs). This is typically caused by exp…
Domain-decomposed Bayesian inversion based on local Karhunen-Loève expansions
Zhihang Xu, Qifeng Liao, Jinglai Li
In many Bayesian inverse problems the goal is to recover a spatially varying random field. Such problems are often computationally challenging especially when the forward model is…
Deep neural network based adaptive learning for switched systems
Junjie He, Zhihang Xu, Qifeng Liao
In this paper, we present a deep neural network based adaptive learning (DNN-AL) approach for switched systems. Currently, deep neural network based methods are actively developed…
N3H-Core: Neuron-designed Neural Network Accelerator via FPGA-based Heterogeneous Computing Cores
Yu Gong, Zhihan Xu, Zhezhi He +4
Accelerating the neural network inference by FPGA has emerged as a popular option, since the reconfigurability and high performance computing capability of FPGA intrinsically satis…