Filling in the white space: Spatial interpolation with Gaussian processes and social media data von Giorgi, Salvatore, Eichstaedt, Johannes C., Preoţiuc-Pietro, Daniel, Gardner, Jacob R., Schwartz, H. Andrew, Ungar, Lyle H.

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wenda_gpu: fast domain adaptation for genomic data von Hippen, Ariel A, Crawford, Jake, Gardner, Jacob R, Greene, Casey S

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Determining subpopulation methylation profiles from bisulfite sequencing data of heterogeneous samples using DXM von Fong, Jerry, Gardner, Jacob R, Andrews, Jared M, Cashen, Amanda F, Payton, Jacqueline E, Weinberger, Kilian Q, Edwards, John R

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Active mutual conjoint estimation of multiple contrast sensitivity functions von Marticorena, Dom C P, Wong, Quinn Wai, Browning, Jake, Wilbur, Ken, Davey, Pinakin Gunvant, Seitz, Aaron R, Gardner, Jacob R, Barbour, Dennis L

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Contrast response function estimation with nonparametric Bayesian active learning von Marticorena, Dom C P, Wong, Quinn Wai, Browning, Jake, Wilbur, Ken, Jayakumar, Samyukta, Davey, Pinakin Gunvant, Seitz, Aaron R, Gardner, Jacob R, Barbour, Dennis L

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Fast, Continuous Audiogram Estimation Using Machine Learning von Song, Xinyu D, Wallace, Brittany M, Gardner, Jacob R, Ledbetter, Noah M, Weinberger, Kilian Q, Barbour, Dennis L

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A Novel Method to Identify Epigenetic Subclones with Increased Fitness from Genomic DNA Methylation Data of Lymphoma and Leukemia Patients von Fong, Jerry, Edwards, John R., Gardner, Jacob R., Cashen, Amanda F, Weinberger, Kilian Q., Payton, Jacqueline E.

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Abstract 1222: Efficient domain adaptation for cancer mutation prediction von Hippen, Ariel A., Crawford, Jake, Gardner, Jacob R., Greene, Casey S.

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A Fast, Robust Elliptical Slice Sampling Implementation for Linearly Truncated Multivariate Normal Distributions von Wu, Kaiwen, Gardner, Jacob R

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Understanding Stochastic Natural Gradient Variational Inference von Wu, Kaiwen, Gardner, Jacob R

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Linear Convergence of Black-Box Variational Inference: Should We Stick the Landing? von Kim, Kyurae, Ma, Yian, Gardner, Jacob R

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Demystifying SGD with Doubly Stochastic Gradients von Kim, Kyurae, Ko, Joohwan, Ma, Yi-An, Gardner, Jacob R

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Stochastic Approximation with Biased MCMC for Expectation Maximization von Gruffaz, Samuel, Kim, Kyurae, Durmus, Alain Oliviero, Gardner, Jacob R

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Provably Scalable Black-Box Variational Inference with Structured Variational Families von Ko, Joohwan, Kim, Kyurae, Kim, Woo Chang, Gardner, Jacob R

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A Fast, Robust Elliptical Slice Sampling Implementation for Linearly Truncated Multivariate Normal Distributions von Wu, Kaiwen, Gardner, Jacob R

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Understanding Stochastic Natural Gradient Variational Inference von Wu, Kaiwen, Gardner, Jacob R

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The Behavior and Convergence of Local Bayesian Optimization von Wu, Kaiwen, Kim, Kyurae, Garnett, Roman, Gardner, Jacob R

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Practical and Matching Gradient Variance Bounds for Black-Box Variational Bayesian Inference von Kim, Kyurae, Wu, Kaiwen, Oh, Jisu, Gardner, Jacob R

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Computation-Aware Gaussian Processes: Model Selection And Linear-Time Inference von Wenger, Jonathan, Wu, Kaiwen, Hennig, Philipp, Gardner, Jacob R, Pleiss, Geoff, Cunningham, John P

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Local Bayesian optimization via maximizing probability of descent von Nguyen, Quan, Wu, Kaiwen, Gardner, Jacob R, Garnett, Roman

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