PROBPROG2020

Thursday October 22nd

ID Floor Poster Type
6 1 Soss: Declarative Probabilistic Programming via Runtime Code Generation [pdf]
Chad Scherrer (RelationalAI)*, Taine Zhao (University of Tsukuba) 		Extended Abstract
12 1 Approximations in Probabilistic Programs: a Compositional Nonasymptotic analysis of Nested MCMC [pdf]
Ekansh Sharma (University of Toronto)*, Daniel M. Roy (University of Toronto) 		Extended Abstract
14 1 Optimal approximate sampling for probabilistic programming [pdf]
Feras Saad (Massachusetts Institute of Technology), Cameron Freer (Massachusetts Institute of Technology)*, Martin Rinard (MIT), Vikash Mansinghka (Massachusetts Institute of Technology) 		Syndicated Submission
15 1 Near-optimal exact sampling for probabilistic programming [pdf]
Feras Saad (Massachusetts Institute of Technology), Cameron Freer (Massachusetts Institute of Technology)*, Martin Rinard (MIT), Vikash Mansinghka (Massachusetts Institute of Technology) 		Syndicated Submission
18 1 Mixed Hamiltonian Monte Carlo for Mixed Discrete and Continuous Variables [pdf]
Guangyao Zhou (Vicarious AI)* 		Extended Abstract
19 1 Amortized Population Gibbs Samplers with Neural Sufficient Statistics [pdf]
Hao Wu (Northeastern University)*, Heiko Zimmermann (Northeastern University), Eli Sennesh (Northeastern University), Tuan Anh Le (MIT), Jan-Willem van de Meent (Northeastern University) 		Extended Abstract
21 1 PyTorch-Struct: A library for efficient deep structured prediction [pdf]
Alexander Rush (Harvard)* 		Extended Abstract
27 1 tfp.mcmc: Modern Markov Chain Monte Carlo Tools Built for Modern Hardware [pdf]
Junpeng Lao (Google), Christopher Suter (Google), Ian Langmore (Google), Cyril Chimisov (Google), Ashish Saxena (Google), Pavel Sountsov (Google), Dave Moore (Google), Rif A. Saurous (), Matthew D Hoffman (Google), Joshua V Dillon (Google)* 		Extended Abstract
28 1 Modular Exact Inference for Discrete Probabilistic Programs [pdf]
Steven J Holtzen (University of California, Los Angeles)*, Guy Van den Broeck (UCLA), Todd Millstein (UCLA) 		Extended Abstract
32 1 Compiling Stan to Generative Probabilistic Languages [pdf]
Guillaume Baudart (IBM Research)*, Javier Burroni (UMass Amherst), Martin Hirzel (IBM Research), Kiran Kate (IBM Research), Louis Mandel (IBM Research), Avraham Shinnar (IBM Research) 		Extended Abstract
33 2 Nested Reasoning About Autonomous Agents [pdf]
Iris R Seaman (Northeastern University)*, Jan-Willem van de Meent (Northeastern University), David Wingate (Brigham Young University) 		Extended Abstract
35 1 Automated Posterior Interval Evaluation for Inference in Probabilistic Programming [pdf]
Edward K Kao (MIT-LL)*, Michael Yee (MIT-LL) 		Extended Abstract
37 1 Structured Conditional Continuous Normalizing Flows [pdf]
Christian Weilbach (University of British Columbia)*, Boyan Beronov (University of British Columbia), William S G Harvey (University of British Columbia), Frank Wood (University of British Columbia) 		Syndicated Submission
39 1 A Multilevel Bayesian Model for Precision Oncology
Asher Wasserman (xCures)*, Jeff Shrager (xCures), Mark Shapiro (xCures), Al Musella (The Musella Foundation For Brain Tumor Research & Information) 		Extended Abstract
40 1 Deep Probabilistic Surrogate Networks for Universal Simulator Approximation [pdf]
Andreas Munk (University of British Columbia)*, Adam Scibior (University of British Columbia), Atilim Gunes Baydin (University of Oxford), Andrew Stewart (Convergent Manufacturing Technologies Inc.), Goran Fernlund (Convergent Manufacturing Technologies Inc.), Anoush Poursartip (University of British Columbia), Frank Wood (University of British Columbia) 		Extended Abstract
41 1 Probabilistic analysis of experimental DEER spectroscopy data for protein structure determination [pdf]
Stephan Pribitzer (University of Washington)*, Sarah Sweger (University of Washington), Stefan Stoll (University of Washington) 		Extended Abstract
42 1 Joint Distributions for TensorFlow Probability [pdf]
Dan Piponi (Google)*, Dave Moore (Google), Joshua V Dillon (Google) 		Extended Abstract
43 1 Analysis of Distributed Training of Bayesian Neural Networks at Scale [pdf]
Himanshu Sharma (Argonne National Lab)*, Elise Jennings (Argonne National Lab) 		Extended Abstract
44 1 PClean: Probabilistic Scripts for Automating Common-Sense Data Cleaning [pdf]
Alexander K. Lew (MIT)*, Monica N Agrawal (MIT), Vikash Mansinghka (Massachusetts Institute of Technology) 		Syndicated Submission
47 1 PPLBench: Evaluation Framework For Probabilistic Programming Languages [pdf]
Sourabh Kulkarni, Kinjal Divesh Shah, Nimar Arora, Xiaoyan Wang, Yucen Lily Li, Nazanin Khosravani Tehrani, Michael Tingley, David Noursi, Narjes Torabi, Sepehr Akhavan Masouleh, Eric Lippert, Erik Meijer 		Extended Abstract
49 1 Delayed Sampling via Barriers and Funsors [pdf]
Fritz Obermeyer (Uber AI Labs)*, Eli Bingham (Uber AI Labs) 		Extended Abstract
50 2 Eff-Bayes: ProbProg with built-in effect handlers
Oliver Goldstein (King's College London), Žiga Lukšič (University of Ljubljana), Matija Pretnar (University of Ljubljana), Daan Leijen (Microsoft Research Redmond), Ohad Kammar (University of Oxford)*, Adam Scibior (University of British Columbia) 		Extended Abstract
51 2 Bean Machine: A Declarative Probabilistic Programming Language For Efficient Programmable Inference [pdf]
Nazanin Tehrani, Nimar S. Arora, Yucen Lily Li, Kinjal Divesh Shah, David Noursi, Michael Tingley, Narjes Torabi, Sepehr Masouleh, Eric Lippert, Erik Meijer 		Extended Abstract
52 2 Probabilistic Programming by Transformation in JAX [pdf]
Sharad Vikram (Google)*, Alexey Radul (Google), Matthew D Hoffman (Google) 		Extended Abstract
53 2 Structured differentiable models of 3D scenes via generative scene graphs [pdf]
Ben Zinberg (Massachusetts Institute of Technology)*, Marco Cusumano-Towner (), Vikash Mansinghka (Massachusetts Institute of Technology) 		Syndicated Submission
54 2 A Bayesian Computation Graph for High-Performance Gradient Evaluation on the JVM
Avi Bryant (Gradient Retreat)* 		Extended Abstract
55 2 FunMC: A functional API for building Markov Chains [pdf]
Pavel Sountsov (Google)*, Alexey Radul (Google) 		Extended Abstract
58 2 A Language for Counterfactual Generative Models
Zenna Tavares (MIT)*, James Koppel (MIT), Xin Zhang (MIT), Armando Solar-Lezama (MIT) 		Extended Abstract
59 2 A Probabilistic Programming Approach to Selection of TV Shows for Linear Advertising
Ritwik Mitra (AT&T Labs - Research)* 		Extended Abstract
70 2 Probabilistic Programs with Stochastic Conditioning [pdf]
David Tolpin (Ben Gurion University of the Negev & PUB+)*, Hongseok Yang (KAIST), Yuan Zhou (University of Oxford) 		Extended Abstract
73 2 Translating Recursive Probabilistic Programs to Factor Graph Grammars [pdf]
David Chiang (University of Notre Dame), Chung-chieh Shan (Indiana University)* 		Extended Abstract
74 2 Dynamic specialization for trace-based probabilistic programming systems [pdf]
McCoy R Becker (Charles River Analytics)* 		Extended Abstract
78 2 The Base Measure Problem and its Solution [pdf]
Alexey Radul (Google)*, Boris Alexeev (Google) 		Extended Abstract
79 2 Towards Causal Psychophysiology in the Wild: Probabilistic Programs for Skin Conductance Analysis [pdf]
David Ramsay (MIT Media Lab)*, Patrick Chwalek (MIT Media Lab), Jan-Willem van de Meent (Northeastern University), Joseph Paradiso (MIT Media Lab) 		Extended Abstract
80 2 Bayesian classification and modeling of single-molecule fluorescence images using Pyro [pdf]
Yerdos Ordabayev (Brandeis University)*, Larry Friedman (Brandeis University), Douglas Theobald (Brandeis University), Jeff Gelles (Brandeis University) 		Extended Abstract

Fri October 23rd

ID Floor Poster Type
3 1 Hierarchical Modelling for High Throughput Protein Engineering [pdf]
Eric ma (Novartis Institutes for Biomedical Research)*, Arkadij Kummer (Novartis Institutes for Biomedical Research ), Richard Lewis (Novartis Institutes for Biomedical Research ) 		Extended Abstract
4 1 Effective Monte Carlo Variational Inference for Binary-Variable Probabilistic Programs [pdf]
Geng Ji (University of California, Irvine)*, Erik B Sudderth (University of California, Irvine) 		Extended Abstract
7 1 A Probabilistic Programming Approach to Protein Structure Superposition [pdf]
Lys Sanz Moreta (University of Copenhagen)*, Thomas Hamelryck (University of Copenhagen), Ahmad Salim Al-Sibahi (University of Copenhagen/Skanned) 		Syndicated Submission
8 1 MultiVerse: Causal Reasoning using Importance Sampling in Probabilistic Programming [pdf]
Yura Perov (Babylon Health)*, Yura Perov (Babylon Health), Logan Graham (University of Oxford), Kostis Gourgoulias (Babylon Health), Jon Richens (Babylon Health), Ciarán Lee (Babylon Health, UCL), Adam Baker (Babylon Health), Saurabh Johri (Babylon Health) 		Syndicated Submission
9 1 Programming Reactive Probabilistic Applications [pdf]
Guillaume Baudart (IBM Research)*, Louis Mandel (IBM Research), Marc Pouzet (ENS), Eric Atkinson (MIT), Benjamin Sherman (MIT), Michael Carbin (MIT) 		Extended Abstract
11 1 Deployable probabilistic programming [pdf]
David Tolpin (Ben Gurion University of the Negev & PUB+)* 		Syndicated Submission
13 1 Automated statistical tests for probabilistic programs [pdf]
Feras Saad (Massachusetts Institute of Technology), Cameron Freer (Massachusetts Institute of Technology)*, Nate Ackerman (Harvard University), Vikash Mansinghka (Massachusetts Institute of Technology) 		Syndicated Submission
16 1 ArviZ: backend agnostic exploratory analysis of Bayesian models in Python [pdf]
Oriol Abril Pla (ArviZ)*, Alex Andorra (ArviZ), Agustina Arroyuelo (Instituto de Matemática Aplicada San Luis, UNSL-CONICET), Seth Axen (University of California, San Francisco), Colin Carroll (Freebird, Inc), Piyush Gautam (NIT Hamirpur), Ari Hartikainen (Aalto University), Ravin Kumar (ArviZ), Osvaldo A Martin (Instituto de Matemática Aplicada San Luis, UNSL-CONICET), Mitzi Morris (Institute for Social and Economic Research and Policy, Columbia University), Aki Vehtari (Department of Computer Science, Aalto University). 		Extended Abstract
17 1 Efficient inference with discrete parameters in Stan [pdf]
Maria I Gorinova (University of Edinburgh)*, Andy Gordon (Microsoft Research), Charles Sutton (Google), Matthijs Vakar (University of Oxford) 		Extended Abstract
22 1 Probabilistic programming for birth-death models of evolution using an alive particle filter with delayed sampling [pdf]
Jan Kudlicka (Uppsala University)*, Lawrence M Murray (Uber AI), Fredrik Ronquist (Swedish Museum of Natural History), Thomas Schön (Uppsala University) 		Syndicated Submission
23 1 Divide, Conquer, and Combine: a New Inference Strategy for Probabilistic Programs with Stochastic Support
Yuan Zhou (University of Oxford)*, Hongseok Yang (KAIST), Yee Whye Teh (University of Oxford), Tom Rainforth (University of Oxford) 		Extended Abstract
24 1 Higher-Order Probabilistic Programming and Name Generation [pdf]
Marcin Sabok (McGill University), Sam Staton (University of Oxford), Dario M Stein (University of Oxford)*, Michael Wolman (McGill University) 		Extended Abstract
25 1 SPLog: Sum-Product Logic [pdf]
Arseny Skryagin (TU Darmstadt)*, Karl Stelnez (TU Darmstadt), Alejandro Molina (TU Darmstadt), Fabrizio G Ventola (TU Darmstadt), Kristian Kersting (TU Darmstadt) 		Extended Abstract
26 1 Bayesian causal inference via probabilistic program synthesis [pdf]
Sam A Witty (University of Massachusetts, Amherst)*, Alexander K. Lew (MIT), David Jensen (University of Massachusetts Amherst), Vikash Mansinghka (Massachusetts Institute of Technology) 		Extended Abstract
29 1 Compilation of Universal Probabilistic Programs to GPGPUs [pdf]
Daniel Lundén (KTH Royal Institute of Technology)*, Joey Öhman (KTH Royal Institute of Technology), David Broman () 		Extended Abstract
30 1 DynamicPPL: Stan-like speed for dynamic probabilistic models [pdf]
Mohamed Tarek (University of New South Wales, Canberra, Australia), Kai Xu (University of Edinburgh), Martin Trapp (Graz University of Technology), Hong Ge (University of Cambridge)*, Zoubin Ghahramani (University of Cambridge) 		Extended Abstract
34 1 The Design of Scruff: A Framework for AI Based on Probabilistic Programming [pdf]
Avi Pfeffer (Charles River Analytics)*, Jarred Barber (Charles River Analytics), McCoy Becker (Charles River Analytics), Joe Campolongo (Charles River Analytics), Joe Gorman (Charles River Analytics), Michael R Harradon (Charles River Analytics), Kenneth Lu (Charles River Analytics), Steve Wacks (Charles River Analytics) 		Extended Abstract
36 1 Lazy Structured Factored Inference: A Highly General Algorithm for Probabilistic Program Inference
Avi Pfeffer (Charles River Analytics)*, Brian Ruttenberg (formerly of Charles River Analytics), William Kretschmer (University of Texas) 		Extended Abstract
45 1 A Monad for Point Processes [pdf]
Swaraj Dash (University of Oxford)*, Sam Staton (University of Oxford) 		Extended Abstract
46 1 AdvancedHMC.jl: A robust, modular and efficient implementation of advanced HMC algorithms [pdf]
Kai Xu (University of Edinburgh)*, Mohamed Tarek (University of New South Wales, Canberra, Australia), Martin Trapp (Graz University of Technology), Hong Ge (University of Cambridge), Zoubin Ghahramani (University of Cambridge), William Tebbutt (University of Cambridge) 		Syndicated Submission
48 2 Functional Tensors for Probabilistic Programming [pdf]
Fritz Obermeyer (Uber AI Labs), Eli Bingham (Uber AI Labs)*, Martin Jankowiak (Uber AI Labs), Du Phan (UIUC), Jonathan Chen (-) 		Extended Abstract
56 2 Subproblem pseudomarginal reversible jump MCMC in probabilistic programming languages [pdf]
Marco Cusumano-Towner (Massachusetts Institute of Technology)*, Alexander K. Lew (MIT), Vikash Mansinghka (Massachusetts Institute of Technology) 		Extended Abstract
57 2 TyXe : Pyro-Based Bayesian Neural Networks for Pytorch Users in 5 Lines of Code [pdf]
Hippolyt Ritter (University College London), Theofanis Karaletsos (Uber AI Labs)* 		Extended Abstract
60 2 A design proposal for InferenceQL: an SQL-like probabilistic programming language [pdf]
Ulrich Schaechtle (MIT)*, Zane Shelby (MIT), Vikash Mansinghka (Massachusetts Institute of Technology) 		Extended Abstract
61 2 Composable Effects for Flexible and Accelerated Probabilistic Programming in NumPyro [pdf]
Du Phan (UIUC)*, Neeraj Pradhan (Uber AI Labs), Martin Jankowiak (Uber AI Labs) 		Extended Abstract
63 2 Attention for Inference Compilation [pdf]
William S G Harvey (University of British Columbia)*, Andreas Munk (University of British Columbia), Atilim Gunes Baydin (University of Oxford), Alexander Bergholm ( University of British Columbia), Frank Wood (University of British Columbia) 		Extended Abstract
64 2 Amortized Rejection Sampling in Universal Probabilistic Programming [pdf]
Saeid Naderiparizi (University of British Columbia)*, Adam Scibior (University of British Columbia), Andreas Munk (University of British Columbia), Mehrdad Ghadiri (GeorgiaTech), Atilim Gunes Baydin (University of Oxford), Bradley J Gram-Hansen (University of Oxford), Christian A Schroeder de Witt (University of Oxford), Rob Zinkov (University of Oxford), Philip Torr (University of Oxford), Tom Rainforth (University of Oxford), Yee Whye Teh (University of Oxford), Frank Wood (University of British Columbia) 		Extended Abstract
65 2 Assessing Re-Identification Risks using Probabilistic Programming (Extended Abstract) [pdf]
Raúl Pardo (IT University of Copenhagen)*, Willard Rafnsson (IT University of Copenhagen), Christian Probst (Unitec Institute of Technology), Andrzej Wąsowski (IT University of Copenhagen) 		Extended Abstract
66 2 Auxiliary-Variable Programmable Inference [pdf]
Alexander K. Lew (MIT)*, Benjamin Sherman (MIT), Marco Cusumano-Towner (), Michael Carbin (MIT), Vikash Mansinghka (Massachusetts Institute of Technology) 		Extended Abstract
67 2 Almost surely terminating probabilistic programs are differentiable almost everywhere [pdf]
Carol Mak (University of Oxford), Luke Ong (University of Oxford), Hugo Paquet (University of Oxford)* 		Extended Abstract
69 2 Probabilistic Programming with Lea [pdf]
Pierre Denis (independent scholar)* 		Extended Abstract
71 2 EinStein VI: General Stein Variational Inference in NumPyro [pdf]
Ahmad Salim Al-Sibahi (University of Copenhagen)*, Ola Rønning (University of Copenhagen), Christophe Ley (Ghent University), Thomas Hamelryck (University of Copenhagen) 		Extended Abstract
72 1 Bayesian Policy Search for Stochastic Domains [pdf]
David Tolpin (Ben Gurion University of the Negev & PUB+)*, Yuan Zhou (University of Oxford), Hongseok Yang (KAIST) 		Extended Abstract
76 2 SYMPAIS: Symbolic Adaptive Importance Sampling for Probabilistic Program Analysis [pdf]
Yicheng Luo (Imperial College London)*, Antonio Filieri (Imperial College London), Yuan Zhou (University of Oxford) 		Extended Abstract
77 2 Inverse Cognition in Search and Rescue using Probabilsitic Programming [pdf]
Kenneth Lu (Charles River Analytics)* 		Extended Abstract
82 2 Structural time series grammar over variable blocks [pdf]
DavId R Dewhurst (Charles River Analytics)* 		Extended Abstract
83 2 An embeddable uncertainty module for strategy game [pdf]
Yueyi Zhuo (NJUST)* 		Extended Abstract

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