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We present a method to downscale idealized geophysical fluid simulations using generative models based on diffusion maps. By analyzing the Fourier spectra of images drawn from different data distributions, we show how one can chain together…

Machine Learning · Computer Science 2023-05-04 Tobias Bischoff , Katherine Deck

Understanding flood probabilities is essential to making sound decisions about flood-risk management. Many people rely on flood probability maps to inform decisions about purchasing flood insurance, buying or selling real-estate,…

Applications · Statistics 2020-12-22 Mahkameh Zarekarizi , K. Joel Roop-Eckart , Sanjib Sharma , Klaus Keller

We present an open-source Matlab framework, titled iFluid, for simulating the dynamics of integrable models using the theory of generalized hydrodynamics (GHD). The framework provides an intuitive interface, enabling users to define and…

Statistical Mechanics · Physics 2020-03-18 Frederik S. Møller , Jörg Schmiedmayer

We present an efficient solver for massively-parallel direct numerical simulations of incompressible turbulent flows. The method uses a second-order, finite-volume pressure-correction scheme, where the pressure Poisson equation is solved…

Fluid Dynamics · Physics 2019-09-13 Pedro Costa

We present the Douglas-Rachford algorithm as a successful heuristic for solving graph coloring problems. Given a set of colors, these type of problems consist in assigning a color to each node of a graph, in such a way that every pair of…

Optimization and Control · Mathematics 2016-12-16 Francisco J. Aragón Artacho , Rubén Campoy

Flooding is the world's most costly type of natural disaster in terms of both economic losses and human causalities. A first and essential procedure towards flood monitoring is based on identifying the area most vulnerable to flooding,…

We define a new impartial combinatorial game, Flag Coloring, based on flood filling. We then generalize to a graph game, and find values for many positions on two colors. We demonstrate that the generalized game is PSPACE-complete for two…

Combinatorics · Mathematics 2022-12-22 Kyle Burke , Craig Tennenhouse

We study the clustering of bipartite graphs and Boolean matrix factorization in data streams. We consider a streaming setting in which the vertices from the left side of the graph arrive one by one together with all of their incident edges.…

Machine Learning · Computer Science 2020-12-08 Stefan Neumann , Pauli Miettinen

A finite element approach to the elastic flow of a curve coupled with a diffusion equation on the curve is analysed. Considering the graph case, the problem is weakly formulated and approximated with continuous linear finite elements, which…

Numerical Analysis · Mathematics 2017-07-28 Paola Pozzi , Björn Stinner

Burning and cooling are diffusion processes on graphs in which burned (or cooled) vertices spread to their neighbors with a new source picked at discrete time steps. In burning, the one tries to burn the graph as fast as possible, while in…

Graph-based semi-supervised learning usually involves two separate stages, constructing an affinity graph and then propagating labels for transductive inference on the graph. It is suboptimal to solve them independently, as the correlation…

Computer Vision and Pattern Recognition · Computer Science 2019-02-19 Qilin Li , Senjian An , Ling Li , Wanquan Liu

Many problems can be presented in an abstract form through a wide range of binary objects and relations which are defined over problem domain. In these problems, graphical demonstration of defined binary objects and solutions is the most…

Graphics · Computer Science 2016-03-24 Mohammadreza Ashouri , Ali Golshani , Dara Moazzmi , Mandana Ghasemi

This paper deals with a time-split explicit/implicit approach for solving a two-dimensional hydrodynamic flow model with appropriate initial and boundary conditions. The time-split technique is employed to upwind the convection term and to…

Numerical Analysis · Mathematics 2024-12-18 Eric Ngondiep

Transitivity is a central, generative principle in social and other complex networks, capturing the tendency for two nodes with a common neighbor to form a direct connection. We propose a new model for highly dense, complex networks based…

Social and Information Networks · Computer Science 2026-02-02 Anthony Bonato , MacKenzie Carr , Ketan Chaudhary , Trent G. Marbach , Teddy Mishura

Diffusion and flow-driven instability, or transport-driven instability, is one of the central mechanisms to generate inhomogeneous gradient of concentrations in spatially distributed chemical systems. However, verifying the transport-driven…

Systems and Control · Electrical Eng. & Systems 2020-03-05 Yutaka Hori , Hiroki Miyazako

This paper considers the noncooperative maximization of mutual information in the Gaussian interference channel in a fully distributed fashion via game theory. This problem has been studied in a number of papers during the past decade for…

Information Theory · Computer Science 2016-11-17 Gesualdo Scutari , Daniel P. Palomar , Sergio Barbarossa

In algorithmic graph theory, a classic open question is to determine the complexity of the Maximum Independent Set problem on $P_t$-free graphs, that is, on graphs not containing any induced path on $t$ vertices. So far, polynomial-time…

Data Structures and Algorithms · Computer Science 2018-04-12 Gábor Bacsó , Daniel Lokshtanov , Dániel Marx , Marcin Pilipczuk , Zsolt Tuza , Erik Jan van Leeuwen

We call a system bouncing ball billiard if it consists of a particle that is subjected to a constant vertical force and bounces inelastically on a one-dimendional vibrating periodically corrugated floor. Here we choose circular scatterers…

Chaotic Dynamics · Physics 2007-05-23 L. Matyas , R. Klages

Given an inverse problem with a normalizing flow prior, we wish to estimate the distribution of the underlying signal conditioned on the observations. We approach this problem as a task of conditional inference on the pre-trained…

Machine Learning · Statistics 2021-06-16 Jay Whang , Erik M. Lindgren , Alexandros G. Dimakis

In this work, physics-informed neural networks are applied to incompressible two-phase flow problems. We investigate the forward problem, where the governing equations are solved from initial and boundary conditions, as well as the inverse…

Fluid Dynamics · Physics 2021-01-26 Aaron B. Buhendwa , Stefan Adami , Nikolaus A. Adams
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