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Model-based metrics: Sample-efficient estimates of predictive model subpopulation performance.

, , , and . MLHC, volume 149 of Proceedings of Machine Learning Research, page 308-336. PMLR, (2021)

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Stochastic Gradient MCMC Methods for Hidden Markov Models., , and . ICML, volume 70 of Proceedings of Machine Learning Research, page 2265-2274. PMLR, (2017)Learning the Parameters of Determinantal Point Process Kernels., , , and . ICML, volume 32 of JMLR Workshop and Conference Proceedings, page 1224-1232. JMLR.org, (2014)Learning Insulin-Glucose Dynamics in the Wild., , and . MLHC, volume 126 of Proceedings of Machine Learning Research, page 172-197. PMLR, (2020)Modeling the complex dynamics and changing correlations of epileptic events., , and . Artif. Intell., (2014)Bayesian nonparametric learning of complex dynamical phenomena.. Massachusetts Institute of Technology, Cambridge, MA, USA, (2009)ndltd.org (oai:dspace.mit.edu:1721.1/55111).Expectation-Maximization for Learning Determinantal Point Processes., , , and . NIPS, page 3149-3157. (2014)Interpretable Mechanistic Representations for Meal-level Glycemic Control in the Wild., and . ML4H@NeurIPS, volume 225 of Proceedings of Machine Learning Research, page 607-622. PMLR, (2023)Model-based metrics: Sample-efficient estimates of predictive model subpopulation performance., , , and . MLHC, volume 149 of Proceedings of Machine Learning Research, page 308-336. PMLR, (2021)Streaming Variational Inference for Bayesian Nonparametric Mixture Models., , and . AISTATS, volume 38 of JMLR Workshop and Conference Proceedings, JMLR.org, (2015)Adaptively Truncating Backpropagation Through Time to Control Gradient Bias., , and . UAI, volume 115 of Proceedings of Machine Learning Research, page 799-808. AUAI Press, (2019)