Below are a collection of talks, presentations, and podcasts presented by members of the Probabilistic Computing Project.
2023-11-02 AI That Understands the World, Using Probabilistic Programming Vikash Mansinghka at MIT TedX 2023.
2023-06-20 Probabilistic Programming with Stochastic Probabilities Alex Lew at PLDI 2023.
2023-04-25 SMCP3: Sequential Monte Carlo with Probabilistic Program Proposals George Matheos at AISTATS 2023.
2023-01-19 ADEV: Sound Automatic Differentiation of Expected Values of Probabilistic Programs Alex Lew at POPL 2023.
2022-11-04 Scaling Inference Mission: Vikash Mansinghka, MIT Quest for Intelligence At “Advances in the quest to understand intelligence,” held at MIT on Nov. 4, 2022, Vikash Mansinghka presented the background and ideas that led to forming the Scaling Inference Mission.
2021-12-06 3dp3 3DP3: 3D Scene Perception via Probabilistic Programming Nishad Gothoskar at NeurIPS 2021.
2021-07-28 Modeling the Mistakes of Boundedly Rational Agents Within a Bayesian Theory of Mind Tan Zhi Xuan at CogSci 2021.
2021- 07-28 Hierarchical Infinite Relational Model Feras Saad at UAI 2021.
2021-07-28 Julog.jl: Prolog-like Logic Programming in Julia Tan Zhi Xuan at JuliaCon 2021.
2021-07-28 Genify.jl: Transforming Julia into Gen for Bayesian inference Tan Zhi Xuan at JuliaCon 2021.
2021-06-25 SPPL: Probabilistic Programming with Fast Exact Symbolic Inference Feras Saad at PLDI 2021.
2021-04-14 PClean: Bayesian Data Cleaning at Scale with Domain-Specific Probabilistic Programming Alex Lew at AISTATS 2021.
2021-01-17 On the Automatic Derivation of Importance Samplers from Pairs of Probabilistic Programs. Alex Lew at LAFI 2021.
2021-01-10: Transforming Worlds: Automated Involutive MCMC for Open-Universe Probabilistic Models. George Matheos at AABI.
2020-12-06 Online Bayesian Goal Inference for Boundedly Rational Planning Agents Tan Zhi Xuan at NeurIPS 2020.
2020-11-20 AI alignment, philosophical pluralism, and the relevance of non-Western philosophy Tan Zhi Xuan at Effective Altruism Global X EAGxAsia-Pacific 2020.
2020-08-26 The fast loaded dice roller: A near-optimal exact sampler for discrete probability distributions – Feras Saad at AISTATS 2020.
2020-07-16 [Causal Inference using Gaussian Processes with Structured Latent Confounders] Sam Witty at ICML 2020.
2020-05-22 [Gen: A High-Level Programming Platform for Probabilistic Inference] Marco Cusumano-Towner Thesis Defense.
2020-08-26 The fast loaded dice roller: A near-optimal exact sampler for discrete probability distributions – Feras Saad at AISTATS 2020.
2020-01-23 Optimal approximate sampling from discrete probability distributions – Feras Saad at POPL 2020.
2020-01-23 Trace Types and Denotational Semantics for Sound Programmable Inference in Probabilistic Languages – Alex Lew at POPL 2020.
2019-11-20 Probabilistic Programming and Automatic Data Modeling – Feras Saad at Univ. of Notre Dame CICS Seminar Series.
2019-09-14 Probabilistic scripts for automating common-sense tasks – Alex Lew at Strange Loop 2019.
2019-09-14 InferenceQL: AI for data engineers, without the math – Ulrich Schaechtle at Strange Loop 2019.
2019-09-13 New programming constructs for probabilistic AI – Marco Cusumano-Towner at Strange Loop 2019.
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.
2019-06-24: Gen: A General-Purpose Probabilistic Programming System with Programmable Inference – Marco Cusumano-Towner at PLDI 2019.
2019-03-11: Bias in, Bias Out: Building Better AI – SXSW panel discussion including Vikash Mansinghka (audio only)
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.
2018-12-01: Probabilistic programming and meta-programming in Clojure – Vikash Mansinghka at ClojureConj 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 Computable 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
40 https://www.youtube.com/watch?v=Pn4_7nzGhF8