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20192026
most citedDepth separation for reduced deep networks in nonlinear model reduction: Distilling shock waves in nonlinear hyperbolic problems

11 citations · 15 across the 4 of their papers we have counts for

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5 papers · 1 filter

math.NA2024

An explicit spectral decomposition of the ADRT

Weilin Li, Karl Otness, Kui Ren +1

The approximate discrete Radon transform (ADRT) is a hierarchical multiscale approximation of the Radon transform. In this paper, we factor the ADRT into a product of linear transf…

math.NA2024

A Low Rank Neural Representation of Entropy Solutions

Donsub Rim, Gerrit Welper

We construct a new representation of entropy solutions to nonlinear scalar conservation laws with a smooth convex flux function in a single spatial dimension. The representation is…

math.NA202011 cited

Depth separation for reduced deep networks in nonlinear model reduction: Distilling shock waves in nonlinear hyperbolic problems

Donsub Rim, Luca Venturi, Joan Bruna +1

Classical reduced models are low-rank approximations using a fixed basis designed to achieve dimensionality reduction of large-scale systems. In this work, we introduce reduced dee…

math.NA2019

Manifold Approximations via Transported Subspaces: Model reduction for transport-dominated problems

Donsub Rim, Benjamin Peherstorfer, Kyle T. Mandli

This work presents a method for constructing online-efficient reduced models of large-scale systems governed by parametrized nonlinear scalar conservation laws. The solution manifo…

math.NA2019

Exact and fast inversion of the approximate discrete Radon transform from partial data

Donsub Rim

We give an exact inversion formula for the approximate discrete Radon transform introduced in [Brady, SIAM J. Comput., 27(1), 107--119] that is of cost for a square 2…