9 citations · 9 across the 4 of their papers we have counts for
4 papers
Disentangling Attention in Deep Operator Learning: A Controlled Study of Data-Driven and Physics-Informed Architectures
Amar Alem Koric, Qibang Liu, Seid Koric
Deep neural operators learn mappings between input functions and complete PDE solution fields, enabling forward evaluations of new problem instances orders of magnitude faster than…
Single vs. Multiple Branches in DeepONet and S-DeepONet: Network Architecture Follows Coupling in Multiphysics Systems
Jaewan Park, Kazuma Kobayashi, Qibang Liu +3
`Real-time prediction of complex physical systems requires surrogate models that learn from data while representing strong multiphysics coupling. Deep Operator Networks have shown…
An extended ordinary state-based peridynamics for non-spherical horizons
Qibang Liu, Muhao Chen, Robert E. Skelton
This work presents an extended ordinary state-based peridynamics (XOSBPD) model for the non-spherical horizons. Based on the OSBPD, we derive the XOSBPD by introducing the Lagrange…
Adaptive coupling peridynamic least-square minimization with finite element method for fracture analysis
Qibang Liu, X. J. Xin, Jeff Ma
This study presents an adaptive coupling peridynamic least-square minimization with the finite element method (PDLSM-FEM) for fracture analysis. The presented method utilizes the P…