10 citations · 14 across the 5 of their papers we have counts for
5 papers
Causal Convolutional Neural Networks as Finite Impulse Response Filters
Kiran Bacsa, Wei Liu, Xudong Jian +2
This study investigates the behavior of Causal Convolutional Neural Networks (CNNs) with quasi-linear activation functions when applied to time-series data characterized by multimo…
On the Rate of Convergence of Kolmogorov-Arnold Network Regression Estimators
Wei Liu, Eleni Chatzi, Zhilu Lai
Kolmogorov-Arnold Networks (KANs) approximate multivariate functions by composing univariate transformations through additive or multiplicative aggregation. We establish convergenc…
Structured Kolmogorov-Arnold Neural ODEs for Interpretable Learning and Symbolic Discovery of Nonlinear Dynamics
Wei Liu, Kiran Bacsa, Loon Ching Tang +1
Understanding and modeling nonlinear dynamical systems is a fundamental challenge across science and engineering. Deep learning has shown remarkable potential for capturing complex…
Using Graph Neural Networks and Frequency Domain Data for Automated Operational Modal Analysis of Populations of Structures
Xudong Jian, Yutong Xia, Gregory Duthé +3
The Population-Based Structural Health Monitoring (PBSHM) paradigm has recently emerged as a promising approach to enhance data-driven assessment of engineering structures by facil…
Discussing the Spectrum of Physics-Enhanced Machine Learning; a Survey on Structural Mechanics Applications
Marcus Haywood-Alexander, Wei Liu, Kiran Bacsa +2
The intersection of physics and machine learning has given rise to the physics-enhanced machine learning (PEML) paradigm, aiming to improve the capabilities and reduce the individu…