Efficient Online Random Sampling via Randomness Recycling.
CoRR, May, 2025
Efficient Rejection Sampling in the Entropy-Optimal Range.
CoRR, April, 2025
Robust Resource Bounds with Static Analysis and Bayesian Inference.
Proc. ACM Program. Lang., 2024
Programmable MCMC with Soundly Composed Guide Programs.
Proc. ACM Program. Lang., 2024
GenSQL: A Probabilistic Programming System for Querying Generative Models of Database Tables.
Proc. ACM Program. Lang., 2024
Scalable Spatiotemporal Prediction with Bayesian Neural Fields.
CoRR, 2024
Sequential Monte Carlo Learning for Time Series Structure Discovery.
Proceedings of the International Conference on Machine Learning, 2023
Scalable Structure Learning, Inference, and Analysis with Probabilistic Programs
PhD thesis, 2022
Estimators of Entropy and Information via Inference in Probabilistic Models.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022
Hierarchical infinite relational model.
Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021
SPPL: probabilistic programming with fast exact symbolic inference.
Proceedings of the PLDI '21: 42nd ACM SIGPLAN International Conference on Programming Language Design and Implementation, 2021
Optimal approximate sampling from discrete probability distributions.
Proc. ACM Program. Lang., 2020
Exact Symbolic Inference in Probabilistic Programs via Sum-Product Representations.
CoRR, 2020
The Fast Loaded Dice Roller: A Near-Optimal Exact Sampler for Discrete Probability Distributions.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020
Bayesian synthesis of probabilistic programs for automatic data modeling.
Proc. ACM Program. Lang., 2019
Gen: a general-purpose probabilistic programming system with programmable inference.
Proceedings of the 40th ACM SIGPLAN Conference on Programming Language Design and Implementation, 2019
A Family of Exact Goodness-of-Fit Tests for High-Dimensional Discrete Distributions.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019
Temporally-Reweighted Chinese Restaurant Process Mixtures for Clustering, Imputing, and Forecasting Multivariate Time Series.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018
A Bayesian Nonparametric Method for Clustering Imputation, and Forecasting in Multivariate Time Series.
CoRR, 2017
Probabilistic Search for Structured Data via Probabilistic Programming and Nonparametric Bayes.
CoRR, 2017
Detecting Dependencies in Sparse, Multivariate Databases Using Probabilistic Programming and Non-parametric Bayes.
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017
Detecting Dependencies in High-Dimensional, Sparse Databases Using Probabilistic Programming and Non-parametric Bayes.
CoRR, 2016
Probabilistic Data Analysis with Probabilistic Programming.
CoRR, 2016
A Probabilistic Programming Approach To Probabilistic Data Analysis.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016