PROBPROG 2018
The International Conference on Probabilistic Programming
- Program
- Schedule
- Posters
- Registration (SOLD OUT)
- Conduct
Program Overview
- Thursday October 4th: Industry discussions, Tutorials, Open-source meetup.
- Friday October 5th: Statistics track, Practice track.
- Saturday October 6th: Intelligence track, Languages and Systems track.
Thursday October 4th
The Industry Day will take place in the McGovern Institute for Brain and Cognitive Science at MIT.
| Start | End | Activity | Location |
|---|---|---|---|
10:00 |
Registration |
||
10:30 |
10:40 |
Welcome |
|
10:40 |
12:00 |
Speed Networking |
|
12:00 |
13:00 |
Lunch Break |
|
13:00 |
14:30 |
Tutorial by Vikash Mansinghka |
|
14:30 |
15:00 |
Coffee Break and Networking |
|
15:00 |
16:30 |
Industry Discussions |
|
15:00 |
16:30 |
Developer Meetup |
Friday October 5th
The Practice of Probabilistic Programming and Statistics and Data Analysis session will take place in MIT Wiesner Building E15.
| Start | End | Activity | Location |
|---|---|---|---|
|
8:00 |
Registration |
Lower Atrium |
|
|
8:40 |
12:00 |
Session: Practice of Probabilistic Programming |
Bartos Theater |
|
8:40 |
9:20 |
Keynote: Zoubin Ghahramani (Uber AI Labs, University of Cambridge) Probabilistic Machine Learning: From theory to industrial impact [video] |
|
|
9:20 |
9:40 |
Talk: Daniel Lee (Stan Development Team, Generable) Dear Stan, I meant to write you sooner but I just been busy [video | slides] |
|
|
9:40 |
10:00 |
Talk: Yordan Zaykov (Microsoft Research) Probabilistic programming in production with Infer.NET [video | slides] |
|
|
10:00 |
10:20 |
Talk: Michael Tingley (Facebook) Probabilistic programming @ FB [video] |
|
|
10:20 |
10:40 |
Coffee Break |
|
|
10:40 |
11:00 |
Talk: Daniel Ritchie (Brown) Probabilistic Programming for Computer Graphics [video | slides] |
|
|
11:00 |
11:20 |
Talk: Dustin Tran (Google) What might deep learners learn from probabilistic programming? [video | slides] |
|
|
11:20 |
11:40 |
Talk: Brooks Paige (Alan Turing Institute, University of Cambridge) Semi-interpretable probabilistic models [video] |
|
|
11:40 |
12:00 |
Talk: Ulrich Schaechtle (MIT) Automated data modeling for science via Bayesian probabilistic program synthesis [video] |
|
|
12:00 |
15:00 |
||
|
15:00 |
18:00 |
Session: Statistics and Data Analysis |
Bartos Theater |
|
15:00 |
15:40 |
Keynote: Dave Blei (Columbia University) Black Box Variational Inference [video | slides] |
|
|
15:40 |
16:00 |
Talk: Lawrence Murray (Uppsala University) Automated learning with a probabilistic programming language: Birch [video] |
|
|
16:00 |
16:20 |
Talk: Dan Roy (University of Toronto) Algorithmic Barriers to Representing Conditional Independence [video] |
|
|
16:20 |
16:40 |
Coffee Break |
|
|
16:40 |
17:00 |
Talk: Tom Rainforth (University of Oxford) Nesting Probabilistic Programs [video | slides] |
|
|
17:00 |
17:20 |
Talk: Maria Gorinova (University of Edinburgh) SlicStan: Optimising Probabilistic Programs using Information Flow Analysis [video | slides] |
|
|
17:20 |
17:40 |
Talk: Hong Ge & Kai Xu (University of Cambridge) The Turing Language for Probabilistic Programming [slides] |
|
|
17:40 |
18:00 |
Talk: Feras Saad (MIT) Bayesian Synthesis of Probabilistic Programs for Automatic Data Modeling [video] |
Saturday October 6th
The Probabilistic Programming and Intelligence and Languages and Systems sessions will take place in MIT Wiesner Building E15.
| Start | End | Activity | Location |
|---|---|---|---|
|
8:00 |
Registration |
Lower Atrium |
|
|
8:40 |
12:00 |
Session: Intelligence |
Bartos Theater |
|
8:40 |
9:20 |
Keynote: Stuart Russell (UC Berkeley) Probabilistic programming and AI [video | slides] |
|
|
9:20 |
9:40 |
Talk: Josh Tenenbaum (MIT) Towards More Human-like Intelligence in Machines [video] |
|
|
9:40 |
10:00 |
Talk: Kristian Kersting (TU Darmstadt) Democratizing Machine Learning using Probabilistic Programming [video | slides] |
|
|
10:00 |
10:20 |
Talk: Frank Wood (University of British Columbia) Inference Compilation [video | slides] |
|
|
10:20 |
10:40 |
Coffee Break |
|
|
10:40 |
11:00 |
Community Announcements and Discussion |
|
|
11:00 |
11:20 |
Talk: Noah Goodman (Uber AI Labs, Stanford) Accelerating science with PPLs for experiment design [video] |
|
|
11:20 |
11:40 |
Talk: Marco Cusumano-Towner (MIT) Gen: A Flexible System for Programming Probabilistic AI [video | slides] |
|
|
11:40 |
12:00 |
Talk: Kevin Ellis (MIT) Growing Libraries of Subroutines with Wake/Sleep Bayesian Program Learning [video | slides] |
|
|
12:00 |
14:40 |
||
|
14:40 |
17:40 |
Session: Languages and Systems |
Bartos Theater |
|
14:40 |
15:20 |
Keynote: Jean-Baptiste Tristan (Oracle Labs) Compilation of Probabilistic Programs [video | slides] |
|
|
15:20 |
15:40 |
Talk: Angelika Kimmig (University of Cardiff) A short introduction to probabilistic logic programming [video] |
|
|
15:40 |
16:00 |
Talk: Hongseok Yang (KAIST) Reparameterization Gradient for Non-differentiable Models from Probabilistic Programming [video | slides] |
|
|
16:00 |
16:20 |
Talk: Chung-Chieh (Ken) Shan (Indiana University) Calculating distributions [video | slides] |
|
|
16:20 |
16:40 |
Coffee Break |
|
|
16:40 |
17:00 |
Talk: Adam Scibior (University of Cambridge) Denotational account of approximate Bayesian inference [video | slides] |
|
|
17:00 |
17:20 |
Talk: Sarah Chasins (UC Berkeley) Data-Driven Synthesis of Full Probabilistic Programs [video] |
|
|
17:20 |
17:40 |
Talk: Eric Atkinson (MIT) Verifying Handcoded Probabilistic Inference Procedures [video] |
|
|
17:40 |
18:00 |
Talk: Timon Gehr (ETH) PSI: Exact Symbolic Inference for Probabilistic Programs |
Sponsors
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