[New Paper] Unified Hysteresis Modeling via Physics-based Deep Learning and Data Augmentation
Published:
Our paper “Unified Hysteresis Modeling via Physics-based Deep Learning and Data Augmentation” has been published in Earthquake Engineering & Structural Dynamics.
The paper proposes a unified hysteresis modeling framework based on deep learning, leveraging a physics-encoded architecture and physics-informed loss functions to capture complex nonlinearities under stochastic excitations.
Citation: Jeon, J., Kwon, O., & Song, J. (2026). “Unified Hysteresis Modeling via Physics-based Deep Learning and Data Augmentation.” Earthquake Engineering & Structural Dynamics. DOI: 10.1002/eqe.70081
