1 citations · 3 across the 9 of their papers we have counts for
10 papers
Control Systems with Model Hierarchies: A Category-Theoretic Framework
Baike She, Tyler Hanks, James Fairbanks +1
Storage functions are widely used to relate a control system to a simpler model for analysis and controller design, and to quantify model mismatch when a controller is designed on…
Heterogeneous Multi-Agent Multi-Target Tracking using Cellular Sheaves
Tyler Hanks, Cristian F. Nino, Joana Bou Barcelo +3
Multi-agent target tracking in the presence of nonlinear dynamics and agent heterogeneity, where state-space dimensions may differ, is a challenging problem that traditional graph…
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…
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…
GATlab: Modeling and Programming with Generalized Algebraic Theories
Owen Lynch, Kris Brown, James Fairbanks +1
Categories and categorical structures are increasingly recognized as useful abstractions for modeling in science and engineering. To uniformly implement category-theoretic mathemat…
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…
Generalized Gradient Descent is a Hypergraph Functor
Tyler Hanks, James Fairbanks, Matthew Klawonn
Cartesian reverse derivative categories (CRDCs) provide an axiomatic generalization of the reverse derivative, which allows generalized analogues of classic optimization algorithms…
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…
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…
A Categorical Representation Language and Computational System for Knowledge-Based Planning
Angeline Aguinaldo, Evan Patterson, James Fairbanks +2
Classical planning representation languages based on first-order logic have preliminarily been used to model and solve robotic task planning problems. Wider adoption of these repre…