88 citations · 94 across the 4 of their papers we have counts for
4 papers
Bayesian Learning to Discover Mathematical Operations in Governing Equations of Dynamic Systems
Hongpeng Zhou, Wei Pan
Discovering governing equations from data is critical for diverse scientific disciplines as they can provide insights into the underlying phenomenon of dynamic systems. This work p…
Sparse Bayesian Deep Learning for Dynamic System Identification
Hongpeng Zhou, Chahine Ibrahim, Wei Xing Zheng +1
This paper proposes a sparse Bayesian treatment of deep neural networks (DNNs) for system identification. Although DNNs show impressive approximation ability in various fields, sev…
A Sparse Bayesian Deep Learning Approach for Identification of Cascaded Tanks Benchmark
Hongpeng Zhou, Chahine Ibrahim, Wei Pan
Nonlinear system identification is important with a wide range of applications. The typical approaches for nonlinear system identification include Volterra series models, nonlinear…
BayesNAS: A Bayesian Approach for Neural Architecture Search
Hongpeng Zhou, Minghao Yang, Jun Wang +1
One-Shot Neural Architecture Search (NAS) is a promising method to significantly reduce search time without any separate training. It can be treated as a Network Compression proble…