most citedA Compositional Framework for First-Order Optimization

1 citations · 1 across the 6 of their papers we have counts for

collaborators

6 papers

math.OC2025

Asynchronous Nonlinear Sheaf Diffusion for Multi-Agent Coordination

Yichen Zhao, Tyler Hanks, Hans Riess +3

Cellular sheaves and sheaf Laplacians provide a far-reaching generalization of graphs and graph Laplacians, resulting in a wide array of applications ranging from machine learning…

cs.CE2025

Porous Convection in the Discrete Exterior Calculus with Geometric Multigrid

Luke Morris, George Rauta, Kevin Carlson +1

The discrete exterior calculus (DEC) defines a family of discretized differential operators which preserve certain desirable properties from the exterior calculus. We formulate and…

math.OC2025

Distributed Multi-agent Coordination over Cellular Sheaves

Tyler Hanks, Hans Riess, Samuel Cohen +3

Techniques for coordination of multi-agent systems are vast and varied, often utilizing purpose-built solvers or controllers with tight coupling to the types of systems involved or…

math.OC20241 cited

A Compositional Framework for First-Order Optimization

Tyler Hanks, Matthew Klawonn, Evan Patterson +2

Optimization decomposition methods are a fundamental tool to develop distributed solution algorithms for large scale optimization problems arising in fields such as machine learnin…

math.NA2024

Decapodes: A Diagrammatic Tool for Representing, Composing, and Computing Spatialized Partial Differential Equations

Luke Morris, Andrew Baas, Jesus Arias +3

We present Decapodes, a diagrammatic tool for representing, composing, and solving partial differential equations. Decapodes provides an intuitive diagrammatic representation of th…

math.CT2024

The diagrammatic presentation of equations in categories

Kevin Arlin, James Fairbanks, Tim Hosgood +1

Lifts of categorical diagrams against discrete opfibrations can be interpreted as presenting solutions to systems…