2 citations · 4 across the 6 of their papers we have counts for
6 papers
Deep Adaptive Bayesian Screening
Jade Lejeune Herman, Arno Strouwen, Johan A. K. Suykens +1
We introduce Deep Adaptive Bayesian Screening (DABS), a method for performing adaptive factorial screening in high-dimensional discrete design spaces. DABS learns a policy network…
Bayesian Symbolic Regression for Missing Physics
Arno Strouwen
Model-based approaches for (bio)process systems often suffer from incomplete knowledge of the underlying physical, chemical, or biological laws. Universal differential equations, w…
Deep Adaptive Model-Based Design of Experiments
Arno Strouwen, Sebastian Micluţa-Câmpeanu
Model-based design of experiments (MBDOE) is essential for efficient parameter estimation in nonlinear dynamical systems. However, conventional adaptive MBDOE requires costly poste…
Adaptive and robust experimental design for linear dynamical models using Kalman filter
Arno Strouwen, Bart M. Nicolaï, Peter Goos
Current experimental design techniques for dynamical systems often only incorporate measurement noise, while dynamical systems also involve process noise. To construct experimental…
A Note on the Output of a Coordinate-Exchange Algorithm for Optimal Experimental Design
Arno Strouwen, Peter Goos
The coordinate-exchange algorithm is commonly used to construct optimal experimental designs. Every execution of the coordinate-exchange algorithm produces a new, seemingly random,…
Experimental Design for Missing Physics
Arno Strouwen, Sebastián Micluţa-Câmpeanu
For most process systems, knowledge of the model structure is incomplete. This missing physics must then be learned from experimental data. Recently, a combination of universal dif…