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In this work a new finite element based Method of Relaxed Streamline Upwinding is proposed to solve hyperbolic conservation laws. Formulation of the proposed scheme is based on relaxation system which replaces hyperbolic conservation laws…

Numerical Analysis · Mathematics 2019-06-05 Ameya D. Jagtap

A family of collective variables is proposed to perform exact dynamical coarse-graining even in systems without time scale separation. More precisely, it is shown that these variables are not slow in general but they satisfy an overdamped…

Statistical Mechanics · Physics 2015-06-19 Jianfeng Lu , Eric Vanden-Eijnden

In this paper, we propose a new numerical method for the underdamped Langevin diffusion (ULD) and present a non-asymptotic analysis of its sampling error in the 2-Wasserstein distance when the $d$-dimensional target distribution…

Machine Learning · Statistics 2025-08-25 Maximilian Scott , Dáire O'Kane , Andraž Jelinčič , James Foster

We present a high-order accurate reconstructed discontinuous Galerkin (rDG) method in arbitrary Lagrangian-Eulerian (ALE) formulation, for solving two-dimensional compressible flows on moving and deforming domains with unstructured curved…

Computational Physics · Physics 2020-05-26 Chuanjin Wang , Hong Luo

Motivated by nonconvex, inconsistent feasibility problems in imaging, the relaxed alternating averaged reflections algorithm, or relaxed Douglas-Rachford algorithm (DR$\lambda$), was first proposed over a decade ago. Convergence results for…

Optimization and Control · Mathematics 2020-03-26 D. Russell Luke , Anna-Lena Martins

In previous work, we introduced a method for determining convergence rates for integration methods for the kinetic Langevin equation for $M$-$\nabla$Lipschitz $m$-log-concave densities [arXiv:2302.10684, 2023]. In this article, we exploit…

Numerical Analysis · Mathematics 2023-06-16 Benedict Leimkuhler , Daniel Paulin , Peter A. Whalley

Exponentiated gradient descent (EGD), a biologically motivated optimisation algorithm that respects Dale's law, produces log-normally distributed synaptic weights at convergence, in alignment with experimental observations in neuroscience.…

Machine Learning · Computer Science 2026-05-26 Nishanth Shetty , Madhava Prasath , Chandra Sekhar Seelamantula

In this paper, we propose a new hybridized discontinuous Galerkin (DG) method for the convection-diffusion problems with mixed boundary conditions. A feature of the proposed method, is that it can greatly reduce the number of…

Numerical Analysis · Mathematics 2013-11-01 Issei Oikawa

As an example of the nonlinear Fokker-Planck equation, the mean field Langevin dynamics recently attracts attention due to its connection to (noisy) gradient descent on infinitely wide neural networks in the mean field regime, and hence the…

Machine Learning · Statistics 2022-02-28 Atsushi Nitanda , Denny Wu , Taiji Suzuki

The first super-convergent hybridisable discontinuous Galerkin (HDG) method for linear elastic problems capable of using the same degree of approximation for both the primal and mixed variables is presented. The key feature of the method is…

Numerical Analysis · Mathematics 2019-08-16 Ruben Sevilla , Matteo Giacomini , Alexandros Karkoulias , Antonio Huerta

We study the relaxation process in normal and anomalous diffusion regimes for systems described by a generalized Langevin equation (GLE). We demonstrate the existence of a very general correlation function which describes the relaxation…

Disordered Systems and Neural Networks · Physics 2007-05-23 Mendeli H. Vainstein , Ismael V. L. Costa , Rafael Morgado , Fernando A. Oliveira

In the first part of this work, we analyzed a Dirichlet boundary control problem for an elliptic convection diffusion PDE and proposed a new hybridizable discontinuous Galerkin (HDG) method to approximate the solution. For the case of a 2D…

Numerical Analysis · Mathematics 2018-07-25 Weiwei Hu , Mariano Mateos , John R. Singler , Xiao Zhang , Yangwen Zhang

We devised a first order time stepping ensemble hybridizable discontinuous Galerkin (HDG) method for a group of parameterized convection diffusion PDEs with different initial conditions, body forces, boundary conditions and coefficients in…

Numerical Analysis · Mathematics 2019-10-24 Gang Chen , Liangya Pi , Yangwen Zhang

Overdamped Langevin dynamics are reversible stochastic differential equations which are commonly used to sample probability measures in high-dimensional spaces, such as the ones appearing in computational statistical physics and Bayesian…

Numerical Analysis · Mathematics 2025-02-10 Tony Lelièvre , Grigorios A. Pavliotis , Geneviève Robin , Régis Santet , Gabriel Stoltz

We investigate a two-parameter hyperbolic relaxation approximation to the incompressible Navier-Stokes equations, incorporating a first-order relaxation and the artificial compressibility method. With vanishingly small perturbations of…

Analysis of PDEs · Mathematics 2026-01-28 Qian Huang , Christian Rohde , Ruixi Zhang

In this paper, we examine the problem of sampling from log-concave distributions with (possibly) superlinear gradient growth under kinetic (underdamped) Langevin algorithms. Using a carefully tailored taming scheme, we propose two novel…

Probability · Mathematics 2025-12-10 Iosif Lytras , Panayotis Mertikopoulos

This work explores optimization methods on hyperbolic manifolds. Building on Riemannian optimization principles, we extend the Hyperbolic Stochastic Gradient Descent (a specialization of Riemannian SGD) to a Hyperbolic Adam optimizer. While…

Machine Learning · Computer Science 2025-10-01 Yanke Wang , Kyriakos Flouris

Purpose: This study aims to assess the accuracy of degree adaptive strategies in the context of incompressible Navier-Stokes flows using the high order hybridisable discontinuous Galerkin (HDG) method. Design/methodology/approach: The work…

Fluid Dynamics · Physics 2024-11-12 Agustina Felipe , Ruben Sevilla , Oubay Hassan

We introduce a new framework of numerical multiscale methods for advection-dominated problems motivated by climate sciences. Current numerical multiscale methods (MsFEM) work well on stationary elliptic problems but have difficulties when…

Computational Engineering, Finance, and Science · Computer Science 2019-05-28 Konrad Simon , Jörn Behrens

In this paper we propose a new approach for sampling from probability measures in, possibly, high dimensional spaces. By perturbing the standard overdamped Langevin dynamics by a suitable Stratonovich perturbation that preserves the…

Numerical Analysis · Mathematics 2019-04-23 Assyr Abdulle , Grigorios A. Pavliotis , Gilles Vilmart
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