Smooth Modeling of Flows on Graphs

Abstract

The high-level goal of this project is to bridge the gap between theoretical developments in the field of optimal transport---designed to understand flows along smooth domains---and the analysis of signals over graphs. In contrast to existing combinatorial algorithms and models for flows on graphs, our approach is inspired by continuous ideas from differential equations, functional analysis, and geometry. In the end, we propose fundamentally different constructions from well-known graph algorithms that more directly link smooth (continuously-varying in time and space) and discrete interpretations of flows.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
May 15, 2020
Accession Number
AD1204561

Entities

People

  • Justin Solomon

Organizations

  • Massachusetts Institute of Technology

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Abstracts
  • Algorithms
  • Applied Mathematics
  • Artificial Intelligence
  • Computational Fluid Dynamics
  • Computational Science
  • Computations
  • Computer Graphics
  • Computer Science
  • Data Processing
  • Deep Learning
  • Differential Equations
  • Electrical Engineering
  • Equations
  • Extrapolation
  • Functional Analysis
  • Geometry
  • Information Operations
  • Linear Programming
  • Machine Learning
  • Massachusetts
  • Military Research
  • Probability Distributions
  • Standards
  • Supervised Machine Learning
  • Theses
  • Three Dimensional
  • Topology
  • Transport Ships
  • Transportation

Readers

  • Distributed Systems and Data Platform Development
  • Graph Algorithms and Convex Optimization.

Technology Areas

  • Space