activity
20132023
most citedModel selection for hybrid dynamical systems via sparse regression

75 citations · 161 across the 11 of their papers we have counts for

collaborators

14 papers

math.NA2023

Random walks in frequency and the reconstruction of obstacles with cavities from multi-frequency data

Travis Askham, Carlos Borges, Jeremy Hoskins +1

Inverse obstacle scattering is the recovery of an obstacle boundary from the scattering data produced by incident waves. This shape recovery can be done by iteratively solving a PD…

math.NA2021

Periodic Fast Multipole Method

Ruqi Pei, Travis Askham, Leslie Greengard +1

A new scheme is presented for imposing periodic boundary conditions on unit cells with arbitrary source distributions. We restrict our attention here to the Poisson, modified Helmh…

math.NA2019★ 23 cited

A Fast Integral Equation Method for the Two-Dimensional Navier-Stokes Equations

Ludvig af Klinteberg, Travis Askham, Mary Catherine Kropinski

The integral equation approach to partial differential equations (PDEs) provides significant advantages in the numerical solution of the incompressible Navier-Stokes equations. In…

math.NA2019

A boundary integral equation approach to computing eigenvalues of the Stokes operator

Travis Askham, Manas Rachh

The eigenvalues and eigenfunctions of the Stokes operator have been the subject of intense analytical investigation and have applications in the study and simulation of the Navier-…

math.DS2018★ 75 cited

Model selection for hybrid dynamical systems via sparse regression

Niall M Mangan, Travis Askham, Steven L Brunton +2

Hybrid systems are traditionally difficult to identify and analyze using classical dynamical systems theory. Moreover, recently developed model identification methodologies largely…

stat.ML2018★ 12 cited

A Unified Framework for Sparse Relaxed Regularized Regression: SR3

Peng Zheng, Travis Askham, Steven L. Brunton +2

Regularized regression problems are ubiquitous in statistical modeling, signal processing, and machine learning. Sparse regression in particular has been instrumental in scientific…