Wednesday 20 October
Session 1
| BST | EDT | PDT | Activity |
|---|---|---|---|
|
15:30 |
10:30 |
7:30 |
Arrival and networking |
|
16:00 |
11:00 |
8:00 |
Welcome: Lawrence Murray & Guy Van den Broeck |
|
16:10 |
11:10 |
8:10 |
Keynote: Katie Bouman (Caltech) Beyond the First Portrait of a Black Hole |
|
16:50 |
11:50 |
8:50 |
Contributed Talk: Guillaume Baudart (Inria Paris, École normale supérieure - PSL University) Automatic Guide Generation for Stan via NumPyro |
|
17:10 |
12:10 |
9:10 |
Contributed Talk: Sam Witty (University of Massachusetts Amherst) Causal Probabilistic Programming Without Tears |
|
17:30 |
12:30 |
9:30 |
Contributed Talk: Feras Saad (Massachusetts Institute of Technology) SPPL: Probabilistic Programming with Fast Exact Symbolic Inference |
|
17:50 |
12:50 |
9:50 |
End |
Session 2
| BST | EDT | PDT | Activity | |
|---|---|---|---|---|
|
18:30 |
13:30 |
10:30 |
Arrival and networking |
|
|
18:45 |
13:45 |
10:45 |
Industry Panel: Impact of Probabilistic Programming Katie Bouman (Caltech), Bob Carpenter (Flatiron), Brian Patton (Google), Omesh Tickoo (Intel), Michael Tingley (Facebook), John Winn (MSR), Veronica Weiner (MIT, moderator) [panelist bios] |
|
|
19:45 |
14:45 |
11:45 |
Posters/Networking |
|
|
21:15 |
16:15 |
13:15 |
End |
Thursday 21 October
Session 3
| BST | EDT | PDT | Activity |
|---|---|---|---|
|
12:30 |
7:30 |
4:30 |
Arrival and networking |
|
13:00 |
8:00 |
5:00 |
Invited Talk: Nicolas Chopin (ENSAE Paris) Probabilistic programming for Sequential Monte Carlo? |
|
13:20 |
8:20 |
5:20 |
Invited Talk: Leah South (Queensland University of Technology) Unbiased and Consistent Nested Sampling via Sequential Monte Carlo |
|
13:40 |
8:40 |
5:40 |
Keynote: John Winn (Microsoft Research) Getting All The Facts: Automated Knowledge Base Construction with a Probabilistic Program |
|
14:20 |
9:20 |
6:20 |
Contributed Talk: Birthe Van den Berg (KU Leuven) From Probabilistic NetKAT to ProbLog: New Algorithms for Inference and Learning in Probabilistic Networks |
|
14:40 |
9:40 |
6:40 |
Contributed Talk: Vincent Dutordoir (University of Cambridge) GPflux: A Library for Deep Gaussian Processes |
|
15:00 |
10:00 |
7:00 |
Contributed Talk: Christian B Thygese (University of Copenhagen / Evaxion Biotech) Efficient Generative Modelling of Protein StructureFragments using a Deep Markov Model |
|
15:20 |
10:20 |
7:20 |
Short break and networking |
|
15:30 |
10:30 |
7:30 |
Posters/Networking |
|
17:00 |
12:00 |
9:00 |
End |
Friday 22 October
Session 4
| BST | EDT | PDT | Activity |
|---|---|---|---|
|
16:30 |
11:30 |
8:30 |
Arrival and networking |
|
17:00 |
12:00 |
9:00 |
Keynote: Bob Carpenter (Flatiron Institute) What do we need from a probabilistic programming language to support Bayesian workflow? |
|
17:40 |
12:40 |
9:40 |
Contributed Talk: Dario M Stein (University of Oxford) Compositional Semantics for Probabilistic Programs with Exact Conditioning |
|
18:00 |
13:00 |
10:00 |
Contributed Talk: Carol Mak (University of Oxford) Nonparametric Hamiltonian Monte Carlo |
|
18:20 |
13:20 |
10:20 |
Contributed Talk: Yu-Hsi Cheng (University of California, Los Angeles) flip-hoisting: A Probabilistic Program Optimization for Exact Inference |
|
18:40 |
13:40 |
10:40 |
Invited Talk: Angelika Kimmig (KU Leuven) Neural probabilistic logic programming |
|
19:00 |
14:00 |
11:00 |
Contributed Talk: Hugo Paquet (University of Oxford) Bayesian strategies: higher-order probabilistic programs as graphical models |
|
19:20 |
14:20 |
11:20 |
Closing Remarks: |
|
19:30 |
14:30 |
11:30 |
End |
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