4 papers
Model synthesis and identifiability analysis of stiff chemical reaction systems with inVAErt networks
Sreejata Dey, Guoxiang Grayson Tong, Jonathan F. MacArt +1
We consider the problem of learning data-driven replicas for stiff systems of ordinary differential equations arising in chemical kinetics that can be evaluated with high computati…
Conditional Normalizing Flows for Forward and Backward Joint State and Parameter Estimation
Luke S. Lagunowich, Guoxiang Grayson Tong, Daniele E. Schiavazzi
Traditional filtering algorithms for state estimation -- such as classical Kalman filtering, unscented Kalman filtering, and particle filters -- show performance degradation when a…
InVAErt networks for amortized inference and identifiability analysis of lumped parameter hemodynamic models
Guoxiang Grayson Tong, Carlos A. Sing Long, Daniele E. Schiavazzi
Estimation of cardiovascular model parameters from electronic health records (EHR) poses a significant challenge primarily due to lack of identifiability. Structural non-identifiab…
InVAErt networks: a data-driven framework for model synthesis and identifiability analysis
Guoxiang Grayson Tong, Carlos A. Sing Long, Daniele E. Schiavazzi
Use of generative models and deep learning for physics-based systems is currently dominated by the task of emulation. However, the remarkable flexibility offered by data-driven arc…