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1
Scala DSLs and Probabilistic Programming
2
Statistics from a Programmer's Perspective
3
What is Stan?
4
Example: Predicting Weight
5
A More Accurate Model?
6
Beyond Simple Regression
7
What is an Embedded DSL?
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Why Embed the DSL?
9
Overview
10
Stan within the Scala Type System
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Creating Stan Types
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Stan Values
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Subclassing is Not Enough
14
Implicits/Type Classes
15
Operator Type-Checking Using Implicits
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Random Number Generation
17
Implicits to Enforce Scope
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Using Scala Types to Check Input Data
19
Detour: The State Monad
20
Type Checking of Stan at Scala Run-Time
21
Conclusion
Description:
Explore probabilistic programming and domain-specific languages in this Strange Loop Conference talk. Dive into Stan, a statistical modeling language, and discover ScalaStan, a novel Scala interface for Stan. Learn how ScalaStan leverages Scala's type system to ensure type-safety and prevent invalid code generation. Examine techniques for embedding domain-specific languages, enforcing scope, and type-checking input data. Gain insights into statistical modeling, Bayesian inference, and the intersection of programming languages and statistics through practical examples and in-depth explanations of key concepts.

Scala DSLs and Probabilistic Programming

Strange Loop Conference
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