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Unsupervised discretization is a crucial step in many knowledge discovery tasks. The state-of-the-art method for one-dimensional data infers locally adaptive histograms using the minimum description length (MDL) principle, but the…

Machine Learning · Computer Science 2022-12-12 Lincen Yang , Mitra Baratchi , Matthijs van Leeuwen

Uncertain partially observable Markov decision processes (uPOMDPs) allow the probabilistic transition and observation functions of standard POMDPs to belong to a so-called uncertainty set. Such uncertainty, referred to as epistemic…

Artificial Intelligence · Computer Science 2021-11-02 Murat Cubuktepe , Nils Jansen , Sebastian Junges , Ahmadreza Marandi , Marnix Suilen , Ufuk Topcu

Finite volume methods for problems involving second order operators with full diffusion matrix can be used thanks to the definition of a discrete gradient for piecewise constant functions on unstructured meshes satisfying an orthogonality…

Numerical Analysis · Mathematics 2016-08-16 Robert Eymard , Thierry Gallouët , Raphaèle Herbin

The Multilevel Monte Carlo (MLMC) method has proven to be an effective variance-reduction statistical method for Uncertainty Quantification (UQ) in Partial Differential Equation (PDE) models, combining model computations at different levels…

Mathematical Software · Computer Science 2023-05-24 Santiago Badia , Jerrad Hampton , Javier Principe

The Fourier Basis Density Model (FBM) was recently introduced as a flexible probability model for band-limited distributions, i.e. ones which are smooth in the sense of having a characteristic function with limited support around the…

Information Theory · Computer Science 2025-05-12 Alfredo De la Fuente , Saurabh Singh , Jona Ballé

We present a fully adaptive multiresolution scheme for spatially one-dimensional quasilinear strongly degenerate parabolic equations with zero-flux and periodic boundary conditions. The numerical scheme is based on a finite volume…

Numerical Analysis · Mathematics 2012-06-22 Raimund Bürger , Ricardo Ruiz Baier , Mauricio Sepúlveda , Kai Schneider

The Poisson-Boltzmann equation (PBE) is a nonlinear elliptic PDE that arises in biomolecular modeling and is a fundamental tool for structural biology. It is used to calculate electrostatic potentials around an ensemble of fixed charges…

Numerical Analysis · Mathematics 2017-10-12 Cleophas Kweyu , Lihong Feng , Matthias Stein , Peter Benner

Symbolic regression that aims to detect underlying data-driven models has become increasingly important for industrial data analysis. For most existing algorithms such as genetic programming (GP), the convergence speed might be too slow for…

Neural and Evolutionary Computing · Computer Science 2017-10-31 Chen Chen , Changtong Luo , Zonglin Jiang

The compact finite difference method is a powerful tool for discretizing conservation laws, owing to its inherent flexibility in developing high-resolution and highly stable schemes. In this paper, we propose a framework for the design of…

Numerical Analysis · Mathematics 2026-03-30 Weifeng Hou , Zhangpeng Sun , Wenqi Yao , Liupeng Wang

We introduce a fluid dynamics algorithm that performs with nearly spectral accuracy, but uses finite-differences instead of FFTs to compute gradients and thus executes 10 times faster. The finite differencing is not based on a high-order…

Astrophysics · Physics 2007-05-23 Jason Maron

The porous medium equation (PME) is a typical nonlinear degenerate parabolic equation. An energetic variational approach has been studied in a recent work [6], in which the trajectory equation is obtained, and a few first order accurate…

Numerical Analysis · Mathematics 2020-06-23 Chenghua Duan , Wenbin Chen , Chun Liu , Cheng Wang , Xingye Yue

This paper develops a probabilistic numerical method for solution of partial differential equations (PDEs) and studies application of that method to PDE-constrained inverse problems. This approach enables the solution of challenging inverse…

Methodology · Statistics 2017-07-12 Jon Cockayne , Chris Oates , Tim Sullivan , Mark Girolami

Probabilistic graphical models (PGMs) are widely used to discover latent structure in data, but their success hinges on selecting an appropriate model design. In practice, model specification is difficult and often requires iterative…

Machine Learning · Computer Science 2026-04-08 Kevin Zhang , Yixin Wang

Cumulative probability models (CPMs) are a robust alternative to linear models for continuous outcomes. However, they are not feasible for very large datasets due to elevated running time and memory usage, which depend on the sample size,…

Computation · Statistics 2022-07-15 Chun Li , Guo Chen , Bryan E. Shepherd

Finite difference schemes for the simulation of elastic waves in materi- als with jump discontinuities are presented. The key feature is the highly accurate treatment of interfaces where media discontinuities arise. The schemes are…

Geophysics · Physics 2013-09-24 Kristoffer Virta , Kenneth Duru

This paper presents a data-driven finite volume method for solving 1D and 2D hyperbolic partial differential equations. This work builds upon the prior research incorporating a data-driven finite-difference approximation of smooth solutions…

Numerical Analysis · Mathematics 2025-02-25 Guillaume de Romémont , Florent Renac , Jorge Nunez , Francisco Chinesta

In this paper we propose the first better than second order accurate method in space and time for the numerical solution of the resistive relativistic magnetohydrodynamics (RRMHD) equations on unstructured meshes in multiple space…

General Relativity and Quantum Cosmology · Physics 2015-05-13 Michael Dumbser , Olindo Zanotti

In this paper we solve numerically a degenerate parabolic equation with dynamical boundary conditions of zero-coupon bond pricing. First, we discuss some properties of the differential equation. Then, starting from the divergent form of the…

Numerical Analysis · Mathematics 2013-07-02 T. Chernogorova , R. Valkov

A method is introduced for the construction of meshless discretization schemes which preserve Lie symmetries of the differential equations that these schemes approximate. The method exploits the fact that equivariant moving frames provide a…

Mathematical Physics · Physics 2015-06-11 Alexander Bihlo

This work combines the consistency in lower-order differential operators with external approximations of functional spaces to obtain error estimates for finite difference finite volume schemes on unstructured non-uniform meshes. This…

Numerical Analysis · Mathematics 2016-12-02 Qingshan Chen
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