Sparse system identification is the data-driven process of obtaining parsimonious differential
equations that describe the evolution of a dynamical system, balancing model complexity …

Weak form equation learning and surrogate modeling has proven to be computationally
efficient and robust to measurement noise in a wide range of applications including ODE …

This manuscript presents a novel approach to nonlinear system identification leveraging
densely defined Liouville operators and a new “kernel” function that represents an …

Many scientific problems can be formulated as sparse regression, ie, regression onto a set
of parameters when there is a desire or expectation that some of the parameters are exactly …

The weak form is a ubiquitous, well-studied, and widely-utilized mathematical tool in modern
computational and applied mathematics. In this work we provide a survey of both the history …

We investigate the benefits and challenges of utilizing the frequency information in
differential equation identification. Solving differential equations and Fourier analysis are …