activity
20122025
most citedA categorical foundation for Bayesian probability

21 citations · 58 across the 10 of their papers we have counts for

collaborators

13 papers

cs.AI2025

Sensemaking in Novel Environments: How Human Cognition Can Inform Artificial Agents

Robert E. Patterson, Regina Buccello-Stout, Mary E. Frame +8

One of the most vital cognitive skills to possess is the ability to make sense of objects, events, and situations in the world. In the current paper, we offer an approach for creat…

eess.SY2025

The Safe Trusted Autonomy for Responsible Space Program

Kerianne L. Hobbs, Sean Phillips, Michelle Simon +11

The Safe Trusted Autonomy for Responsible Space (STARS) program aims to advance autonomy technologies for space by leveraging machine learning technologies while mitigating barrier…

cs.LG2024★ 1 cited

Stacked Universal Successor Feature Approximators for Safety in Reinforcement Learning

Ian Cannon, Washington Garcia, Thomas Gresavage +3

Real-world problems often involve complex objective structures that resist distillation into reinforcement learning environments with a single objective. Operation costs must be ba…

q-bio.NC2023

Representational Tenets for Memory Athletics

Kevin Schmidt, Othalia Larue, Ray Kulhanek +7

We describe the current state of world-class memory competitions, including the methods used to prepare for and compete in memory competitions, based on the subjective report of Wo…

cs.LO2021

Hybrid dynamical type theories for navigation

Paul Gustafson, Jared Culbertson, Daniel E. Koditschek

We present a hybrid dynamical type theory equipped with useful primitives for organizing and proving safety of navigational control algorithms. This type theory combines the framew…

math.CT2019★ 6 cited

Formal composition of hybrid systems

Jared Culbertson, Paul Gustafson, Daniel E. Koditschek +1

We develop a compositional framework for formal synthesis of hybrid systems using the language of category theory. More specifically, we provide mutually compatible tools for hiera…

math.CO2019

Extendable shellability for -dimensional complexes on vertices

Jared Culbertson, Anton Dochtermann, Dan P. Guralnik +1

We prove that for all a shellable -dimensional simplicial complex with at most vertices is extendably shellable. The proof involves considering the structure of…

math.CO2017

Edge Erasures and Chordal Graphs

Jared Culbertson, Dan P. Guralnik, Peter F. Stiller

We prove several results about chordal graphs and weighted chordal graphs by focusing on exposed edges. These are edges that are properly contained in a single maximal complete sub…

cs.LG2016★ 12 cited

Functorial Hierarchical Clustering with Overlaps

Jared Culbertson, Dan P. Guralnik, Peter F. Stiller

This work draws inspiration from three important sources of research on dissimilarity-based clustering and intertwines those three threads into a consistent principled functorial t…

cs.LG2016★ 5 cited

Consistency constraints for overlapping data clustering

Jared Culbertson, Dan P. Guralnik, Jakob Hansen +1

We examine overlapping clustering schemes with functorial constraints, in the spirit of Carlsson--Memoli. This avoids issues arising from the chaining required by partition-based m…

math.MG2015

Injective metrizability and the duality theory of cubings

Jared Culbertson, Dan P. Guralnik, Peter F. Stiller

Following his discovery that finite metric spaces have injective envelopes naturally admitting a polyhedral structure, Isbell, in his pioneering work on injective metric spaces, at…

math.CT2013★ 13 cited

Bayesian machine learning via category theory

Jared Culbertson, Kirk Sturtz

From the Bayesian perspective, the category of conditional probabilities (a variant of the Kleisli category of the Giry monad, whose objects are measurable spaces and arrows are Ma…

math.CT2012★ 21 cited

A categorical foundation for Bayesian probability

Jared Culbertson, Kirk Sturtz

Given two measurable spaces and with countably generated -algebras, a perfect prior probability measure on and a sampling distribution , th…