Conceptual Guides¶
This section provides an introduction to the mathematical and computational foundations of quivers. The guides assume familiarity with basic category theory or a willingness to learn it alongside the material.
Recommended Reading Order¶
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Core Types & Quantales: Start here. Introduces finite sets (SetObject hierarchy), quantales as enrichment algebras, and the algebraic primitives that underpin all morphism composition.
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Morphisms & Composition: Defines what a morphism is as a tensor in \(\mathcal{V}^{|A| \times |B|}\). Covers the morphism hierarchy, composition, and algebraic operations.
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Categorical Structures: Higher-order constructions: functors, natural transformations, adjunctions, monoidal structures, and base change.
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Monads & Comonads: Monadic abstractions (unit, multiply, map), Kleisli categories, algebras, and coalgebras.
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Enriched Category Theory: Advanced structures specific to \(\mathcal{V}\)-enrichment: ends, coends, Kan extensions, weighted limits, profunctors, Yoneda, Day convolution, optics.
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Stochastic Morphisms: The FinStoch category: Markov kernels, conditioned distributions, queries, and the Giry monad.
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Continuous Distributions: ContinuousSpace and ContinuousMorphism: parameterized families, sampled composition, normalizing flows.
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Monadic Programs: Probabilistic programming via sequential draw and let steps, ancestral sampling, and log-joint computation.
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The QVR DSL: Declarative specification of categorical networks: the
.qvrfile format, grammar, and compilation pipeline. -
Variational Inference: Inference pipeline: tracing, conditioning, automatic guides, ELBO, SVI, and predictive sampling.
Quick Navigation¶
- For discrete & finite: Core Types → Morphisms → Categorical
- For probabilistic models: Core Types → Stochastic → Monadic Programs
- For hybrid discrete-continuous: Continuous Distributions → Monadic Programs
- For building models declaratively: The QVR DSL → Variational Inference
- For enriched category theory: Monads & Comonads → Enriched Category Theory