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Sequential Monte Carlo Learning for Time Series Structure Discovery.

, , , , and . ICML, volume 202 of Proceedings of Machine Learning Research, page 29473-29489. PMLR, (2023)

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Scalable Spatiotemporal Prediction with Bayesian Neural Fields., , , , , , and . CoRR, (2024)Estimators of Entropy and Information via Inference in Probabilistic Models., , and . AISTATS, volume 151 of Proceedings of Machine Learning Research, page 5604-5621. PMLR, (2022)Sequential Monte Carlo Learning for Time Series Structure Discovery., , , , and . ICML, volume 202 of Proceedings of Machine Learning Research, page 29473-29489. PMLR, (2023)Detecting Dependencies in Sparse, Multivariate Databases Using Probabilistic Programming and Non-parametric Bayes., and . AISTATS, volume 54 of Proceedings of Machine Learning Research, page 632-641. PMLR, (2017)A Probabilistic Programming Approach To Probabilistic Data Analysis., and . NIPS, page 2011-2019. (2016)Temporally-Reweighted Chinese Restaurant Process Mixtures for Clustering, Imputing, and Forecasting Multivariate Time Series., and . AISTATS, volume 84 of Proceedings of Machine Learning Research, page 755-764. PMLR, (2018)Probabilistic Data Analysis with Probabilistic Programming., and . CoRR, (2016)The Fast Loaded Dice Roller: A Near-Optimal Exact Sampler for Discrete Probability Distributions., , , and . AISTATS, volume 108 of Proceedings of Machine Learning Research, page 1036-1046. PMLR, (2020)Gen: a general-purpose probabilistic programming system with programmable inference., , , and . PLDI, page 221-236. ACM, (2019)Robust Resource Bounds with Static Analysis and Bayesian Inference., , and . Proc. ACM Program. Lang., 8 (PLDI): 76-101 (2024)