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We introduce a novel spatio-temporal discretization for nonlinear Fokker-Planck equations on the multi-dimensional unit cube. This discretization is based on two structural properties of these equations: the first is the representation as a…

Numerical Analysis · Mathematics 2016-01-11 Oliver Junge , Daniel Matthes , Horst Osberger

The free elastic flow is the $L^2$-gradient flow for Euler's elastic energy, or equivalently the Willmore flow with translation invariant initial data. In contrast to elastic flows under length penalisation or preservation, it is more…

Analysis of PDEs · Mathematics 2025-06-24 Tatsuya Miura , Glen Wheeler

We perform numerical analysis of a nonlinear gradient flow, which can be regarded as a parabolic minimal surface problem or a regularised total variation flow, using the gradient discretisation method (GDM). GDM is a unified convergence…

Numerical Analysis · Mathematics 2026-04-21 Jerome Droniou , Kim-Ngan Le , Huateng Zhu

The paper studies integral functionals with non-smooth functions from L_2 defined on solutions of ODEs. Some regularity is obtained in the form of estimates of L_2-norm for these functionals. This result is used for regularization of…

Optimization and Control · Mathematics 2010-11-01 Nikolai Dokuchaev

In this paper, we propose novel algorithms integrated projection-free techniques with accelerated gradient flows to minimize bending energies for nonlinear plates with non-convex metric constraints. We discuss the stability and constraint…

Numerical Analysis · Mathematics 2025-06-18 Guozhi Dong , Hailong Guo , Shuo Yang

We present a paradigm for developing arbitrarily high order, linear, unconditionally energy stable numerical algorithms for gradient flow models. We apply the energy quadratization (EQ) technique to reformulate the general gradient flow…

Numerical Analysis · Mathematics 2020-07-15 Yuezheng Gong , Jia Zhao , Qi Wang

The paper proposes and develops new globally convergent algorithms of the generalized damped Newton type for solving important classes of nonsmooth optimization problems. These algorithms are based on the theory and calculations of…

Optimization and Control · Mathematics 2022-01-20 Pham Duy Khanh , Boris Mordukhovich , Vo Thanh Phat , Dat Ba Tran

Recent advances in inverse problem solving have increasingly adopted flow priors over diffusion models due to their ability to construct straight probability paths from noise to data, thereby enhancing efficiency in both training and…

Computer Vision and Pattern Recognition · Computer Science 2025-11-11 Hossein Askari , Yadan Luo , Hongfu Sun , Fred Roosta

In this paper, we use a generic and general variational method to obtain solutions to the flow of generalized Newtonian fluids through circular pipes and plane slits. The new method is not based on the use of the Euler-Lagrange variational…

Fluid Dynamics · Physics 2015-07-01 Taha Sochi

We propose a fully discrete variational scheme for nonlinear evolution equations with gradient flow structure on the space of finite Radon measures on an interval with respect to a generalized version of the Wasserstein distance with…

Numerical Analysis · Mathematics 2016-09-29 Jonathan Zinsl , Daniel Matthes

We consider Hamiltonian PDEs that can be split into a linear unbounded operator and a regular non linear part. We consider abstract splitting methods associated with this decomposition where no discretization in space is made. We prove a…

Numerical Analysis · Mathematics 2008-11-26 Erwan Faou , Benoit Grebert , Eric Paturel

We introduce a first order Total Variation type regulariser that decomposes a function into a part with a given Lipschitz constant (which is also allowed to vary spatially) and a jump part. The kernel of this regulariser contains all…

Numerical Analysis · Mathematics 2019-12-06 Martin Burger , Yury Korolev , Simone Parisotto , Carola-Bibiane Schönlieb

A fully discrete Lagrangian scheme for numerical solution of the nonlinear fourth order DLSS equation in one space dimension is analyzed. The discretization is based on the equation's gradient flow structure in the $L^2$-Wasserstein metric.…

Numerical Analysis · Mathematics 2014-10-08 Daniel Matthes , Horst Osberger

We study the implicit regularization imposed by gradient descent for learning multi-layer homogeneous functions including feed-forward fully connected and convolutional deep neural networks with linear, ReLU or Leaky ReLU activation. We…

Machine Learning · Computer Science 2018-11-01 Simon S. Du , Wei Hu , Jason D. Lee

This work combines three paradigms of image processing: i) the total variation approach to denoising, ii) the superior structure of hexagonal lattices, and iii) fast and exact graph cut optimization techniques. Although isotropic in theory,…

Optimization and Control · Mathematics 2012-04-18 Clemens Kirisits

This study presents the development of a spatially adaptive weighting strategy for Total Variation regularization, aimed at addressing under-determined linear inverse problems. The method leverages the rapid computation of an accurate…

Numerical Analysis · Mathematics 2025-01-20 Elena Morotti , Davide Evangelista , Andrea Sebastiani , Elena Loli Piccolomini

This is the second in a series of works devoted to small non-selfadjoint perturbations of selfadjoint semiclassical pseudodifferential operators in dimension 2. As in our previous work, we consider the case when the classical flow of the…

Spectral Theory · Mathematics 2007-05-23 Michael Hitrik , Johannes Sjoestrand

We consider the evolution of fronts by mean curvature in the presence of obstacles. We construct a weak solution to the flow by means of a variational method, corresponding to an implicit time-discretization scheme. Assuming the regularity…

Numerical Analysis · Mathematics 2015-06-03 Luís Almeida , Antonin Chambolle , Matteo Novaga

We obtain a complete solution to the problem of classifying all two-dimensional ideal fluid flows with harmonic Lagrangian labelling maps; thus, we explicitly provide all solutions, with the specified structural property, to the…

Mathematical Physics · Physics 2016-04-12 Olivia Constantin , María Martín

An optical flow variational model is proposed for a sequence of images defined on a domain in $\mathbb{R}^2$. We introduce a regularization term given by the $L^1$ norm of a fractional differential operator. To solve the minimization…

Numerical Analysis · Mathematics 2015-12-07 Somayeh Gh. Bardeji , Isabel N. Figueiredo , Ercília Sousa