Compiling Probabilistic Programs with Daphne (by Christian Weilbach)

Oct 12, 2021 · London, United Kingdom

**THIS IS AN ONLINE EVENT**
[Connection details will be shared 1h before the start time]

The London Clojurians are happy to present:

Title: **Compiling Probabilistic Programs with Daphne**
Speaker: **Christian Weilbach**
Time: **[masked] @ 18:30 (London time)**
Local time: https://time.is/1830_12_Oct_2021_in_London/ (click here for local time)

Christian Weilbach (https://whilo.github.io/) will be presenting Daphne.

Clojure is a functional Lisp with strong roots in programming language
research, typically expressed in the form of "languages as libraries"
such as core.logic (Prolog), Datomic/Crux/Datalevin/Datahike
(Datalog), core.async (go-lang) or Anglican (Church). Building on the
general purpose probabilistic programming system provided by Anglican
and the immutability of Clojure, the probabilistic programming
compiler Daphne (https://github.com/plai-group/daphne) is
introduced. Daphne compiles a first order subset of Clojure into an
efficient probabilistic graphical model representation amenable to
Bayesian inference algorithms in Clojure. Alternatively it can be
further compiled to Python and trained as an amortized neural network
artifact. Both the multi-pass compiler and the ability to easily
integrate other languages such as Python are useful not only for
academic research, but also to effectively compile and embed Clojure
into non-JVM production environments.

Christian is a PhD student in probabilistic programming at UBC in
Vancouver. He is currently working on the Daphne compiler and has
ported the probabilistic programming system Anglican to
ClojureScript. In 2018 he cofounded LambdaForge UG and is working with
the team to build a new computational basis for collaborative
self-modeling, a form of democratic cybernetics. A first step in this
direction is the work on the replikativ libraries including Datahike
to provide a unified data management runtime.

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Event organizers
  • London Clojurians

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