Effect Handling for Composable Program Transformations in Edward2

By Dave Moore, Maria I. Gorinova. 2018

16 citations recorded by the source corpus.

Algebraic effects and handlers have emerged in the programming languages community as a convenient, modular abstraction for controlling computational effects. They have found several applications including concurrent programming, meta programming, and more recently, probabilistic programming, as part of Pyro's Poutines library. We investigate the use of effect handlers as a lightweight abstraction for implementing probabilistic programming languages (PPLs). We interpret the existing design of Edward2 as an accidental implementation of an effect-handling mechanism, and extend that design to support nested, composable transformations. We demonstrate that this enables straightforward implementation of sophisticated model transformations and inference algorithms.

Subfields: Artificial Intelligence, Information Systems, Probabilistic & Bayesian Methods

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Neeraj Pradhan
2. Du Phan
3. Martin Jankowiak
4. Andrew Gordon Wilson
5. Wesley J. Maddox

In Probabilistic & Bayesian Methods

1. Neeraj Pradhan
2. Du Phan
3. Martin Jankowiak
4. Andrew Gordon Wilson
5. Wesley J. Maddox

Citations in the corpus

• Composable Effects for Flexible and Accelerated Probabilistic Programming in NumPyro (2019, background): “Effect handlers have emerged as a composable abstraction for program transformations in PPLs [2, 11, 12].”