Discrepancy Modeling Framework: Learning missing physics, modeling systematic residuals, and disambiguating between deterministic and random effects

10 March 2022

Papers citing "Discrepancy Modeling Framework: Learning missing physics, modeling systematic residuals, and disambiguating between deterministic and random effects"

6 / 6 papers shown

Title
Deep learning for model correction of dynamical systems with data scarcity Caroline Tatsuoka Dongbin Xiu 18 0 0 23 Oct 2024
Structural Constraints for Physics-augmented Learning Simon Kuang Xinfan Lin PINN 26 0 0 07 Oct 2024
Response Estimation and System Identification of Dynamical Systems via Physics-Informed Neural Networks M. Haywood-Alexander Giacamo Arcieri A. Kamariotis Eleni Chatzi 21 1 0 02 Oct 2024
Correcting model misspecification in physics-informed neural networks (PINNs) Zongren Zou Xuhui Meng George Karniadakis PINN 16 40 0 16 Oct 2023
Low-dimensional Data-based Surrogate Model of a Continuum-mechanical Musculoskeletal System Based on Non-intrusive Model Order Reduction Jonas Kneifl D. Rosin Oliver Röhrle Jörg Fehr AI4CE 19 13 0 13 Feb 2023
Auto-differentiable Ensemble Kalman Filters Yuming Chen D. Sanz-Alonso Rebecca Willett 32 33 0 16 Jul 2021