2 citations · 12 across the 14 of their papers we have counts for
14 papers
Implicit Neural Representations and the Algebra of Complex Wavelets
T. Mitchell Roddenberry, Vishwanath Saragadam, Maarten V. de Hoop +1
Implicit neural representations (INRs) have arisen as useful methods for representing signals on Euclidean domains. By parameterizing an image as a multilayer perceptron (MLP) on E…
Resolvent Estimates for Viscoelastic Systems of Extended Maxwell Type and their Applications
Maarten V. de Hoop, Masato Kimura, Ching-Lung Lin +1
In the theory of viscoelasticity, an important class of models admits a representation in terms of springs and dashpots. Widely used members of this class are the Maxwell model and…
Coupling of flow, contact mechanics and friction, generating waves in a fractured porous medium
Maarten V. de Hoop, Kundan Kumar
We present a mixed dimensional model for a fractured poro-elasic medium including contact mechanics. The fracture is a lower dimensional surface embedded in a bulk poro-elastic mat…
Globally injective and bijective neural operators
Takashi Furuya, Michael Puthawala, Matti Lassas +1
Recently there has been great interest in operator learning, where networks learn operators between function spaces from an essentially infinite-dimensional perspective. In this wo…
Early-warning inverse source problem for the elasto-gravitational equations
Lorenzo Baldassari, Maarten V. de Hoop, Elisa Francini +1
Through coupled physics, we study an early-warning inverse source problem for the elasto-gravitational equations. It consists of a mixed hyperbolic-elliptic system of partial diffe…
Deep Invertible Approximation of Topologically Rich Maps between Manifolds
Michael Puthawala, Matti Lassas, Ivan Dokmanic +2
How can we design neural networks that allow for stable universal approximation of maps between topologically interesting manifolds? The answer is with a coordinate projection. Neu…