Category theory for scientists (Old version)
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There are many books designed to introduce category theory to either a mathematical audience or a computer science audience. In this book, our audience is the broader scientific community. We attempt to show that category theory can be applied throughout the sciences as a framework for modeling phenomena and communicating results. In order to target the scientific audience, this book is example-based rather than proof-based. For example, monoids are framed in terms of agents acting on objects, sheaves are introduced with primary examples coming from geography, and colored operads are discussed in terms of their ability to model self-similarity. A new version with solutions to exercises will be available through MIT Press.
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Cited by 5 Pith papers
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Quantifying Spacetime Integration across a Partition with Synergy
Synergy-based measures from partial information decomposition are found more suitable than current practice for quantifying integration in simple deterministic networks for the Information Integration Theory of Consciousness.
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Quantifying Spacetime Integration across a Partition with Synergy
Synergy-based measures of spacetime integration outperform current IIT practice when tested on simple deterministic networks.
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Hausdorff and Wasserstein metrics on graphs and other structured data
Defines Hausdorff-style and Wasserstein-style metrics on C-sets, proving the latter are convex relaxations of the former and computable as linear programs.
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Quantifying Spacetime Integration across a Partition with Synergy
Introduces four synergy-based measures of spacetime integration from partial information decomposition and finds them more suitable than current IIT practice for simple deterministic networks.
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A category-theoretic approach to modeling John Cage's Silent piece
The paper uses functors and a pushout in category theory to derive a schema S for John Cage's Silent piece from categories representing specific compositions.
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