Below are a collection of talks, presentations, and podcasts presented by members of the Probabilistic Computing Project.
2019-07-25. Gen: A General-Purpose Probabilistic Programming System – Alex Lew at JuliaCon 2019.
2019-07-23. Cleaning Messy Data with Julia and Gen – Alex Lew at JuliaCon 2019.
2019-01-17. Bayesian Synthesis of Probabilistic Programs for Automatic Data Modeling – Feras Saad at POPL 2019.
2018-12-06. Gen: A Flexible System for Programming Probabilistic AI – Marco Cusumano-Towner at PROBPROG 2018.
2018-10-05. Bayesian Synthesis of Probabilistic Programs for Automatic Data Modeling – Feras Saad at PROBPROG 2018.
2018-10-05. Automated data modeling for science via Bayesian probabilistic program synthesis – Ulrich Schaechtle at PROBPROG 2018.
2018-06-22. Probabilistic Programming with Programmable Inference – Vikash Mansinghka at PLDI 2018.
2017-12-04. Engineering and Reverse-Engineering Intelligence Using Probabilistic Programs, Program Induction, and Deep Learning – Joshua Tenenbaum and Vikash Mansinghka at NIPS 2017.
2017-06-04. AI Assisted Data Analysis for Humanitarian Causes – Vikash Mansinghka at Effective Altruism (EA) Global, Boston.
2016-12-01: Introducing model-based thinking into AI systems – Vikash Mansinghka and Ben Lorica on The O’Reilly Data Show Podcast.
2016-10-06: Probabilistic Programming for Augmented Intelligence – Vikash Mansinghka at the Simons Institute for Theory of Computing.
2016-10-04: Three Problems in Computabl Probability Theory – Cameron Freer at the Simons Institute for Theory of Computing.
2016-03-15: Probabilistic Programming for Augmented Intelligence – Vikash Mansinghka at the MIT Media Lab.
2015-10-28: BayesDB: Query the Probable Implications of Data – Marco Cusumano-Towner and Feras Saad at the Future Programming Workshop.
2015-09-24: An Overview of Probabilistic Programming – Vikash Mansighka at Strange Loop.
2015-09-24: BayesDB: Query the Probable Implications of Data – Richard Tibbetts at Strange Loop.
2015-02-17: A Survey of Probabilistic Programming – Vikash Mansinghka at Columbia Data Science