Search Results for author: Brynjulf Owren

Found 6 papers, 2 papers with code

Learning Hamiltonians of constrained mechanical systems

1 code implementation31 Jan 2022 Elena Celledoni, Andrea Leone, Davide Murari, Brynjulf Owren

Recently, there has been an increasing interest in modelling and computation of physical systems with neural networks.

Lie Group integrators for mechanical systems

no code implementations25 Feb 2021 Elena Celledoni, Ergys Çokaj, Andrea Leone, Davide Murari, Brynjulf Owren

Finally, we show how Lie group integrators can be applied to model the controlled path of a payload being transported by two rotors.

Image Registration Numerical Analysis Numerical Analysis Dynamical Systems 65L05, 70E55

Equivariant neural networks for inverse problems

1 code implementation23 Feb 2021 Elena Celledoni, Matthias J. Ehrhardt, Christian Etmann, Brynjulf Owren, Carola-Bibiane Schönlieb, Ferdia Sherry

In this work, we demonstrate that group equivariant convolutional operations can naturally be incorporated into learned reconstruction methods for inverse problems that are motivated by the variational regularisation approach.

Inductive Bias

An integral model based on slender body theory, with applications to curved rigid fibers

no code implementations21 Dec 2020 Helge I. Andersson, Elena Celledoni, Laurel Ohm, Brynjulf Owren, Benjamin K. Tapley

We propose a novel integral model describing the motion of curved slender fibers in viscous flow, and develop a numerical method for simulating dynamics of rigid fibers.

Fluid Dynamics Numerical Analysis Numerical Analysis

Structure preserving deep learning

no code implementations5 Jun 2020 Elena Celledoni, Matthias J. Ehrhardt, Christian Etmann, Robert I McLachlan, Brynjulf Owren, Carola-Bibiane Schönlieb, Ferdia Sherry

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 tasks.

Deep learning as optimal control problems: models and numerical methods

no code implementations11 Apr 2019 Martin Benning, Elena Celledoni, Matthias J. Ehrhardt, Brynjulf Owren, Carola-Bibiane Schönlieb

We review the first order conditions for optimality, and the conditions ensuring optimality after discretisation.

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