most citedUsing discrete Darboux polynomials to detect and determine preserved measures and integrals of rational maps

13 citations · 15 across the 2 of their papers we have counts for

collaborators

5 papers

cs.LG2020

Structure preserving deep learning

Elena Celledoni, Matthias J. Ehrhardt, Christian Etmann +4

Over the past few years, deep learning has risen to the foreground as a topic of massive interest, mainly as a result of successes obtained in solving large-scale image processing…

math.DG2019

Signatures in Shape Analysis: an Efficient Approach to Motion Identification

Elena Celledoni, Pål Erik Lystad, Nikolas Tapia

Signatures provide a succinct description of certain features of paths in a reparametrization invariant way. We propose a method for classifying shapes based on signatures, and com…

physics.flu-dyn20192 cited

A slender body model for thin rigid fibers: validation and comparisons

Laurel Ohm, Benjamin K. Tapley, Helge I. Andersson +2

In this paper we consider a computational model for the motion of thin, rigid fibers in viscous flows based on slender body theory. Slender body theory approximates the fluid veloc…

math.OC2019

Deep learning as optimal control problems: models and numerical methods

Martin Benning, Elena Celledoni, Matthias J. Ehrhardt +2

We consider recent work of Haber and Ruthotto 2017 and Chang et al. 2018, where deep learning neural networks have been interpreted as discretisations of an optimal control problem…

nlin.SI201913 cited

Using discrete Darboux polynomials to detect and determine preserved measures and integrals of rational maps

E Celledoni, C Evripidou, D I McLaren +4

In this Letter we propose a systematic approach for detecting and calculating preserved measures and integrals of a rational map. The approach is based on the use of cofactors and…