68 citations · 81 across the 6 of their papers we have counts for
6 papers
Kolmogorov-Arnold Network Autoencoders
Mohammadamin Moradi, Shirin Panahi, Erik Bollt +1
Deep learning models have revolutionized various domains, with Multi-Layer Perceptrons (MLPs) being a cornerstone for tasks like data regression and image classification. However,…
Data-driven model discovery with Kolmogorov-Arnold networks
Mohammadamin Moradi, Shirin Panahi, Erik M. Bollt +1
Data-driven model discovery of complex dynamical systems is typically done using sparse optimization, but it has a fundamental limitation: sparsity in that the underlying governing…
Random forests for detecting weak signals and extracting physical information: a case study of magnetic navigation
Mohammadamin Moradi, Zheng-Meng Zhai, Aaron Nielsen +1
It was recently demonstrated that two machine-learning architectures, reservoir computing and time-delayed feed-forward neural networks, can be exploited for detecting the Earth's…
Machine-learning prediction of tipping with applications to the Atlantic Meridional Overturning Circulation
Shirin Panahi, Ling-Wei Kong, Mohammadamin Moradi +4
Anticipating a tipping point, a transition from one stable steady state to another, is a problem of broad relevance due to the ubiquity of the phenomenon in diverse fields. The ste…
Machine-learning parameter tracking with partial state observation
Zheng-Meng Zhai, Mohammadamin Moradi, Bryan Glaz +2
Complex and nonlinear dynamical systems often involve parameters that change with time, accurate tracking of which is essential to tasks such as state estimation, prediction, and c…
Model-free tracking control of complex dynamical trajectories with machine learning
Zheng-Meng Zhai, Mohammadamin Moradi, Ling-Wei Kong +3
Nonlinear tracking control enabling a dynamical system to track a desired trajectory is fundamental to robotics, serving a wide range of civil and defense applications. In control…