4 papers
An efficient Quasi-Newton method for nonlinear inverse problems via learned singular values
Danny Smyl, Tyler N. Tallman, Dong Liu +1
Solving complex optimization problems in engineering and the physical sciences requires repetitive computation of multi-dimensional function derivatives. Commonly, this requires co…
Learning and correcting non-Gaussian model errors
Danny Smyl, Tyler N. Tallman, Jonathan A. Black +2
All discretized numerical models contain modelling errors - this reality is amplified when reduced-order models are used. The ability to accurately approximate modelling errors inf…
Optimizing electrode positions in 2D Electrical Impedance Tomography using deep learning
Danny Smyl, Dong Liu
Electrical Impedance Tomography (EIT) is a powerful tool for non-destructive evaluation, state estimation, and process tomography - among numerous other use cases. For these applic…
OpenQSEI: a MATLAB package for Quasi Static Elasticity Imaging
Danny Smyl, Sven Bossuyt, Dong Liu
Quasi Static Elasticity Imaging (QSEI) aims to computationally reconstruct the inhomogeneous distribution of the elastic modulus using a measured displacement field. QSEI is a well…