Evan Patterson

According to our database, Evan Patterson authored at least 26 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Decapodes: A diagrammatic tool for representing, composing, and computing spatialized partial differential equations.

Luke Morris, Andrew Baas, Jesus Arias, Maia Gatlin, Evan Patterson, James P. Fairbanks

J. Comput. Sci., 2024

Automating Transfer of Robot Task Plans using Functorial Data Migrations.

Angeline Aguinaldo, Evan Patterson, William Regli

CoRR, 2024

GATlab: Modeling and Programming with Generalized Algebraic Theories.

Owen Lynch, Kristopher Brown, James P. Fairbanks, Evan Patterson

CoRR, 2024

Representing Knowledge and Querying Data using Double-Functorial Semantics.

Michael Lambert, Evan Patterson

CoRR, 2024

A compositional account of motifs, mechanisms, and dynamics in biochemical regulatory networks.

Rebekah Aduddell, James P. Fairbanks, Amit Kumar, Pablo S. Ocal, Evan Patterson, Brandon T. Shapiro

Compositionality, 2024

Modeling Model Predictive Control: A Category Theoretic Framework for Multistage Control Problems.

Tyler Hanks, Baike She, Evan Patterson, Matthew Hale, Matthew Klawonn, James P. Fairbanks

Proceedings of the American Control Conference, 2024

2023

Computational category-theoretic rewriting.

Kristopher Brown, Evan Patterson, Tyler Hanks, James P. Fairbanks

J. Log. Algebraic Methods Program., August, 2023

A Categorical Representation Language and Computational System for Knowledge-Based Planning.

Angeline Aguinaldo, Evan Patterson, James P. Fairbanks, Jaime Ruiz

CoRR, 2023

Structured and Decorated Cospans from the Viewpoint of Double Category Theory.

Evan Patterson

Proceedings of the Sixth International Conference on Applied Category Theory 2023, 2023

2022

Compositional Modeling with Stock and Flow Diagrams.

John Baez, Xiaoyan Li, Sophie Libkind, Nathaniel Osgood, Evan Patterson

Proceedings of the Proceedings Fifth International Conference on Applied Category Theory, 2022

An Algebraic Framework for Structured Epidemic Modeling.

Sophie Libkind, Andrew Baas, Micah Halter, Evan Patterson, James P. Fairbanks

CoRR, 2022

2021

Double pushout rewriting of C-sets.

Kristopher Brown, Evan Patterson, James P. Fairbanks

CoRR, 2021

Categorical Data Structures for Technical Computing.

Evan Patterson, Owen Lynch, James P. Fairbanks

CoRR, 2021

Operadic Modeling of Dynamical Systems: Mathematics and Computation.

Sophie Libkind, Andrew Baas, Evan Patterson, James P. Fairbanks

Proceedings of the Fourth International Conference on Applied Category Theory, 2021

2020

Wiring diagrams as normal forms for computing in symmetric monoidal categories.

Evan Patterson, David I. Spivak, Dmitry Vagner

Proceedings of the 3rd Annual International Applied Category Theory Conference 2020, 2020

The algebra and machine representation of statistical models.

Evan Patterson

CoRR, 2020

Compositional Scientific Computing with Catlab and SemanticModels.

Micah Halter, Evan Patterson, Andrew Baas, James P. Fairbanks

CoRR, 2020

String Diagrams for Assembly Planning.

Jade Master, Evan Patterson, Shahin Yousfi, Arquimedes Canedo

Proceedings of the Diagrammatic Representation and Inference, 2020

2019

Graph Representation Ensemble Learning.

Palash Goyal, Di Huang, Sujit Rokka Chhetri, Arquimedes Canedo, Jaya Shree, Evan Patterson

CoRR, 2019

Reports of the AAAI 2019 Spring Symposium Series.

Ioana Baldini, Clark W. Barrett, Antonio Chella, Carlos Cinelli, David Gamez, Leilani H. Gilpin, Knut Hinkelmann, Dylan Holmes, Takashi Kido, Murat Kocaoglu, William F. Lawless, Alessio Lomuscio, Jamie C. Macbeth, Andreas Martin, Ranjeev Mittu, Evan Patterson, Donald Sofge, Prasad Tadepalli, Keiki Takadama, Shomir Wilson

AI Mag., 2019

Conformalized Quantile Regression.

Yaniv Romano, Evan Patterson, Emmanuel J. Candès

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018

Teaching machines to understand data science code by semantic enrichment of dataflow graphs.

Evan Patterson, Ioana Baldini, Aleksandra Mojsilovic, Kush R. Varshney

CoRR, 2018

Semantic Representation of Data Science Programs.

Evan Patterson, Ioana Baldini, Aleksandra Mojsilovic, Kush R. Varshney

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

2017

Dataflow representation of data analyses: Toward a platform for collaborative data science.

Evan Patterson, Robert N. McBurney, H. Schmidt, Ioana Baldini, Aleksandra Mojsilovic, Kush R. Varshney

IBM J. Res. Dev., 2017

Knowledge Representation in Bicategories of Relations.

Evan Patterson

CoRR, 2017

Machine Representation of Data Analyses: Towards a Platform for Collaborative Data Science.

Evan Patterson, Ioana Baldini, Aleksandra Mojsilovic, Kush R. Varshney

Proceedings of the 2017 AAAI Spring Symposia, 2017