StanCon 2019 Schedule

Tuesday, August 20, Tutorials

  • 8:00am-9:00am Registration
  • 9:00am-11:30am Tutorials with Break
    • Track 1: Basics of Bayesian inference and Stan.
    • Track 2: Stan for Programmers.
    • Track 3: Hierarchical Modeling with Stan.
  • 11:30am-12:30pm Open Developers Meeting (loo, projpred, bayesplot, discourse)
  • 12:30pm-2:00pm Provided Lunch
  • 2:00pm-4:30pm Tutorials with Break
    • Track 1: Basics of Bayesian inference and Stan.
    • Track 2: A Dive into Stan’s C++ Model Concept.
    • Track 3: Population and ODE-based models using Stan and Torsten.
  • 4:30pm-5:30pm Open Developers Meeting (posteriordb = reference model and posterior database, bayesbenchr = framework for benchmarking inference algorithms)

Wednesday, August 21, Tutorials

  • 8:00am-9:00am Registration
  • 9:00am-11:30am Tutorials with Break
    • Track 1: Basics of Bayesian inference and Stan.
    • Track 2: Stan for Programmers.
    • Track 3: Hierarchical Modeling with Stan.
  • 11:30am-12:30pm Open Developers Meeting, (bayesflow for Bayesian workflow, parallelization, optimization, KINSOL solver)
  • 12:30pm-2:00pm Provided Lunch
  • 2:00pm-4:30pm Tutorials with Break
    • Track 1: Basics of Bayesian inference and Stan.
    • Track 2: Model assessment and selection.
    • Track 3: Population and ODE-based models using Stan and Torsten.
  • 4:30pm-5:30pm Open Developers Meeting, (sparse matrices, Laplace for GLVMs)

Thursday, August 22, Conference

  • 8:00am-9:00am Registration
  • 9:00am-10:00am Submitted Talks
    • Prior choice in logit models of discrete choice. Jim Savage.  Abstract  Video
    • Approximate leave-future-out cross-validation for Bayesian time series models. Paul Bürkner, Jonah Gabry, Aki Vehtari.  Abstract  Video
    • The Currency of Place and the Short-Term Rental Market. Mikael Brunila.  Abstract  Video
  • 10:00am-10:40am Break
  • 10:40am-11:40am Submitted Talks
    • Modelling enzyme kinetics with Stan. Teddy Groves. DTU BIOSUSTAIN Quantitative Modelling of Cell Metabolism Team  Abstract  Video
    • The emergence of HIV resistance to antiretroviral therapy in southern Africa: a mechanistic meta-analysis of survey data. Julien Riou, Matthias Egger, Christian Althaus. Institute of Social and Preventive Medicine, University of Bern, Switzerland  Abstract  Video
    • Handling missing data, censored values and measurement error in machine learning models using multiple imputation for early stage drug discovery. Rowan Swiers. AstraZeneca  Abstract  Video
  • 11:40am-12:00pm Sponsor Talks and Birds of Feather
  • 12:00pm-1:00pm Provided Lunch
  • 1:00pm-2:00pm Stan Community Meeting
  • 2:00pm-3:00pm Submitted Talks
    • Fast Forward Like a Lambo (skrrt skrrt). Daniel Lee. Generable  Abstract  Video
    • Profit-Maximizing A/B Tests. Elea McDonnell Feit, Ron Berman. Drexel University, The Wharton School  Abstract  Video
    • When seasonality meets Bayesian: Decomposing seasonalities in Stan. Hyunji Moon, SNU, Hyeonseop Lee, PUBG.  Abstract  Video
  • 3:00pm-3:40pm Break
  • 3:40pm-4:20pm Submitted Talks
    • Chronikis: a Bayesian time-series modeling language. Kevin S. Van Horn. Adobe Inc.  Abstract, Docker link  Video
    • Estimating the prevalence of HIV infection in England using Bayesian evidence synthesis. Anne Presanis, Christopher Jackson (presenting author), Daniela De Angelis (MRC Biostatistics Unit, University of Cambridge); Peter Kirwan, Alison Brown, Ada Miltz, Ross Harris, Cuong Chau, Stephanie Migchelsen, Hamish Mohammed, Katy Davison, Sara Croxford, Sarika Desai, Kathy Lowndes, Valerie Delpech, Noel Gill (Public Health England).  Abstract  Video
  • 4:20pm-5:10pm David Spiegelhalter Communicating Uncertainty about Facts, Numbers and Science  Video
  • 5:10pm-6:30pm Networking at the Pub and pickup football (soccer) match
  • 6:30pm Dinner at King’s College

Friday, August 23

  • 8:00am-9:00am Registration
  • 9:00am-10:00am Submitted Talks
    • Extending Stan’s Automatic Differentiation (AD) capabilities using dco/c++. Philip Maybank. Numerical Algorithms Group (NAG)  Abstract  Video
    • The State of GPU Computation Support for Stan. Rok Češnovar (University of Ljubljana - UL), Steve Bronder (Capital One), Davor Sluga (UL), Jure Demšar (UL), Tadej Ciglarič (UL), Sean Talts (Columbia University), Erik Štrumbelj (UL).  Abstract  Video
    • Modeling cocoa bean fermentation processes. Mauricio Moreno-Zambrano, Sergio Grimbs, Matthias S. Ullrich, and Marc-Thorsten Hütt. Department of Life Sciences & Chemistry, Jacobs University Bremen  Abstract  Video
  • 10:00am-10:40am Break
  • 10:40am-12:00pm Submitted Talks
    • Bayesian analyses of time-to-event data using the rstanarm R package. Eren M. Elçi, Sam Brilleman. Public Health and Preventive Medicine, Monash University  Abstract  Video
    • A Decision-Theoretic Journey From Early Clinical Data to Late Stage Efficacy using Hierarchical Joint Models. Krzysztof Sakrejda, Eric Novik. Generable  Abstract  Video
    • Stacking for multimodal posterior distributions. Yuling Yao, Aki Vehtari, and Andrew Gelman.  Abstract  Video
    • Bayesian leave-one-out cross-validation for large data. Måns Magnusson (Aalto), Michael Riis Andersen (Danish Technical University), Johan Jonasson (Chalmers Technical University), Aki Vehtari (Aalto).  Abstract  Video
  • 12:00pm-1:00pm Provided Lunch
  • 1:00pm-2:00pm Open Developers Meeting, (stanc optimization)
  • 2:00pm-3:00pm Submitted Talks
    • Simulation of Statistic Mechanical Systems using Stan. Forrest Eli Hurley. North Carolina State University  Abstract  Video
    • Structured priors for survey estimates in the presence of non-representative data. Yuxiang Gao (University of Toronto), Lauren Kennedy (Columbia University), Daniel Simpson (University of Toronto).  Abstract  Video
    • Prediction and causal inference for time-to-event outcomes truncated by death. Leah Comment.  Abstract  Video
  • 3:00pm-3:40pm Break
  • 3:40pm-4:00pm Submitted Talk
    • Getting the Lead out–Does New York City’s childhood lead testing make statistical sense? Jonathan Auerbach, Breck Baldwin. Columbia University  Abstract  Video
  • 4:00pm-4:50pm Lauren Kennedy Out of Sample Prediction and the Quest for Generalization  Video

Invited speakers

David Spiegelhalter, will speak on “Communicating Uncertainty about Facts, Numbers and Science”

Lauren Kennedy, will speak on “Out of sample prediction and the quest for generalization”

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