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Discrete distributions, particularly in high-dimensional deep models, are often highly multimodal due to inherent discontinuities. While gradient-based discrete sampling has proven effective, it is susceptible to becoming trapped in local…

Machine Learning · Computer Science 2024-10-28 Patrick Pynadath , Riddhiman Bhattacharya , Arun Hariharan , Ruqi Zhang

Exponential decay estimates of a general linear weakly damped wave equation are studied with decay rate lying in a range. Based on the $C^0$-conforming finite element method to discretize spatial variables keeping temporal variable…

Numerical Analysis · Mathematics 2024-06-07 P. Danumjaya , Anil Kumar , Amiya K. Pani

We consider the problem of finding critical points of functions that are non-convex and non-smooth. Studying a fairly broad class of such problems, we analyze the behavior of three gradient-based methods (gradient descent, proximal update,…

Machine Learning · Statistics 2018-04-26 Koulik Khamaru , Martin J. Wainwright

Discrete models usually represent approximations to continuum physics. Cylindrical consistency provides a framework in which discretizations mirror exactly the continuum limit. Being a standard tool for the kinematics of loop quantum…

General Relativity and Quantum Cosmology · Physics 2015-06-05 Bianca Dittrich

We present a new high-order finite volume reconstruction method for hyperbolic conservation laws. The method is based on a piecewise cubic polynomial which provides its solutions a fifth-order accuracy in space. The spatially reconstructed…

Computational Physics · Physics 2017-05-24 Dongwook Lee , Hugues Faller , Adam Reyes

Closed-form differential equations, including partial differential equations and higher-order ordinary differential equations, are one of the most important tools used by scientists to model and better understand natural phenomena.…

Machine Learning · Computer Science 2023-11-30 Krzysztof Kacprzyk , Zhaozhi Qian , Mihaela van der Schaar

We develop a fully discrete, semi-implicit mixed finite element method for approximating solutions to a class of fourth-order stochastic partial differential equations (SPDEs) with non-globally Lipschitz and non-monotone nonlinearities,…

Numerical Analysis · Mathematics 2026-02-17 Beniamin Goldys , Agus L. Soenjaya , Thanh Tran

In this paper, a class of finite difference numerical techniques is presented to solve the second-order linear inhomogeneous damped wave equation. The consistency, stability, and convergences of these numerical schemes are discussed. The…

Numerical Analysis · Mathematics 2021-12-23 Fazel Hadadifard , Satbir Malhi , Zhengyi Xiao

In this note, we present a new numerical method for solving backward stochastic differential equations. Our method can be viewed as an analogue of the classical finite element method solving deterministic partial differential equations.

Probability · Mathematics 2011-06-07 Penghui Wang , Xu Zhang

This paper develops a new framework for designing and analyzing convergent finite difference methods for approximating both classical and viscosity solutions of second order fully nonlinear partial differential equations (PDEs) in 1-D. The…

Numerical Analysis · Mathematics 2013-02-28 Xiaobing Feng , Chiu-Yen Kao , Thomas Lewis

Small-scale features of shallow water flow obtained from direct numerical simulation (DNS) with two different computational codes for the shallow water equations are gathered offline and subsequently employed with the aim of constructing a…

Fluid Dynamics · Physics 2022-02-24 Sagy Ephrati , Erwin Luesink , Golo Wimmer , Paolo Cifani , Bernard Geurts

We discuss the differential equation method for establishing dynamic concentration of discrete random processes. We present several relatively simple examples of it and aim to make the method understandable to the unfamiliar reader who has…

Combinatorics · Mathematics 2022-05-18 Patrick Bennett , Andrzej Dudek

Differentially private selection mechanisms offer strong privacy guarantees for queries aiming to identify the top-scoring element r from a finite set R, based on a dataset-dependent utility function. While selection queries are fundamental…

Machine Learning · Computer Science 2025-04-16 Iago Chaves , Victor Farias , Amanda Perez , Diego Mesquita , Javam Machado

Numerical solutions of differential equations are usually not smooth functions. However, they should resemble the smoothness of the corresponding real solutions in one way or another. In two of our recent papers, a kind of spacial…

Numerical Analysis · Mathematics 2012-07-13 Tong Sun

We propose a new numerical approach to compute nonclassical solutions to hyperbolic conservation laws. The class of finite difference schemes presented here is fully conservative and keep nonclassical shock waves as sharp interfaces,…

Numerical Analysis · Mathematics 2021-10-01 Benjamin Boutin , Christophe Chalons , Frederic Lagoutiere , Philippe G. LeFloch

Despite its numerical challenges, finite element method is used to compute viscous fluid flow. A consensus on the cause of numerical problems has been reached; however, general algorithms---allowing a robust and accurate simulation for any…

Computational Engineering, Finance, and Science · Computer Science 2019-02-05 Bilen Emek Abali

We consider solving nonconvex composite optimization problems in which the sum of a smooth function and a nonsmooth function is minimized. Many of convergence analyses of proximal gradient-type methods rely on global descent property…

Optimization and Control · Mathematics 2026-04-09 Shotaro Yagishita , Masaru Ito

This paper introduces filtered finite difference methods for numerically solving a dispersive evolution equation with solutions that are highly oscillatory in both space and time. We consider a semiclassically scaled nonlinear Schr\"odinger…

Numerical Analysis · Mathematics 2025-08-20 Yanyan Shi , Christian Lubich

The selective frequency damping (SFD) method is an alternative to classical Newton's method to obtain unstable steady-state solutions of dynamical systems. However this method has two main limitations: it does not converge for arbitrary…

Fluid Dynamics · Physics 2015-10-28 Bastien E. Jordi , Colin J. Cotter , Spencer J. Sherwin

Cloud computing is recognized as one of the most promising solutions to information technology, e.g., for storing and sharing data in the web service which is sustained by a company or third party instead of storing data in a hard drive or…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-12-14 A. Roy , A. P. Misra , S. Banerjee