Physics-guided Deep Markov Models for Learning Nonlinear Dynamical Systems with Uncertainty. - Wei Liu; Zhilu Lai; Kiran Bacsa; Eleni N. Chatzi (CoRR, 2021)

Neural Modal ODEs: Integrating Physics-based Modeling with Neural ODEs for Modeling High Dimensional Monitored Structures. - Zhilu Lai; Wei Liu; Xudong Jian; Kiran Bacsa; Limin Sun; Eleni N. Chatzi (CoRR, 2022)

Neural Extended Kalman Filters for Learning and Predicting Dynamics of Structural Systems. - Wei Liu; Zhilu Lai; Kiran Bacsa; Eleni N. Chatzi (CoRR, 2022)

Discussing the Spectra of Physics-Enhanced Machine Learning via a Survey on Structural Mechanics Applications. - Marcus Haywood-Alexander; Wei Liu; Kiran Bacsa; Zhilu Lai; Eleni N. Chatzi (CoRR, 2023)

Using Graph Neural Networks and Frequency Domain Data for Automated Operational Modal Analysis of Populations of Structures. - Xudong Jian; Yutong Xia; Gregory Duthé; Kiran Bacsa; Wei Liu; Eleni N. Chatzi (CoRR, 2024)

Modal Decomposition and Identification for a Population of Structures Using Physics-Informed Graph Neural Networks and Transformers. - Xudong Jian; Kiran Bacsa; Gregory Duthé; Eleni N. Chatzi (CoRR, 2025)

Structured Kolmogorov-Arnold Neural ODEs for Interpretable Learning and Symbolic Discovery of Nonlinear Dynamics. - Wei Liu; Kiran Bacsa; Loon Ching Tang; Eleni N. Chatzi (CoRR, 2025)