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Found 7 papers, 1 papers with code
Probabilistic Graphical Models and Tensor Networks: A Hybrid Framework
We first prove that applying decoherence to the entirety of a BM model converts it into a discrete UGM, and conversely, that any subgraph of a discrete UGM can be represented as a decohered BM.
An enriched category theory of language: from syntax to semantics
In this paper, we propose a mathematical framework for passing from probability distributions on extensions of given texts, such as the ones learned by today's large language models, to an enriched category containing semantic information.
Language Modeling with Reduced Densities
We answer this by constructing a functor from our enriched category of text to a particular enriched category of reduced density operators.
At the Interface of Algebra and Statistics
The starting point is a passage from classical probability theory to quantum probability theory.
Modeling Sequences with Quantum States: A Look Under the Hood
Because it is entangled, the reduced densities that describe subsystems also carry information about the complementary subsystem.
Translating and Evolving: Towards a Model of Language Change in DisCoCat
We unify the product space representation given in (Coecke et al., 2010) and the functorial description in (Kartsaklis et al., 2013), in a way that allows us to view a language as a catalogue of meanings.
What is Applied Category Theory?
This is a collection of introductory, expository notes on applied category theory, inspired by the 2018 Applied Category Theory Workshop, and in these notes we take a leisurely stroll through two themes (functorial semantics and compositionality), two constructions (monoidal categories and decorated cospans) and two examples (chemical reaction networks and natural language processing) within the field.
Category Theory
