5 citations · 5 across the 2 of their papers we have counts for
5 papers
Data-driven learning of non-autonomous systems
Tong Qin, Zhen Chen, John Jakeman +1
We present a numerical framework for recovering unknown non-autonomous dynamical systems with time-dependent inputs. To circumvent the difficulty presented by the non-autonomous na…
Learning reduced systems via deep neural networks with memory
Xiaohan Fu, Lo-Bin Chang, Dongbin Xiu
We present a general numerical approach for constructing governing equations for unknown dynamical systems when only data on a subset of the state variables are available. The unkn…
A Non-Intrusive Correction Algorithm for Classification Problems with Corrupted Data
Jun Hou, Tong Qin, Kailiang Wu +1
A novel correction algorithm is proposed for multi-class classification problems with corrupted training data. The algorithm is non-intrusive, in the sense that it post-processes a…
Data-Driven Deep Learning of Partial Differential Equations in Modal Space
Kailiang Wu, Dongbin Xiu
We present a framework for recovering/approximating unknown time-dependent partial differential equation (PDE) using its solution data. Instead of identifying the terms in the unde…
Deep learning of parameterized equations with applications to uncertainty quantification
Tong Qin, Zhen Chen, John Jakeman +1
We propose a numerical method for discovering unknown parameterized dynamical systems by using observational data of the state variables. Our method is built upon and extends the r…