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07/26/2023
Simulation-based Inference for Cardiovascular Models
Over the past decades, hemodynamics simulators have steadily evolved and...
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02/14/2022
Mapping Interstellar Dust with Gaussian Processes
Interstellar dust corrupts nearly every stellar observation, and account...
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12/01/2021
Learning Invariant Representations with Missing Data
Spurious correlations allow flexible models to predict well during train...
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04/25/2021
Model-based metrics: Sample-efficient estimates of predictive model subpopulation performance
Machine learning models - now commonly developed to screen, diagnose, or...
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04/25/2021
Breiman's two cultures: You don't have to choose sides
Breiman's classic paper casts data analysis as a choice between two cult...
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11/30/2020
Representing and Denoising Wearable ECG Recordings
Modern wearable devices are embedded with a range of noninvasive biomark...
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08/06/2020
Learning Insulin-Glucose Dynamics in the Wild
We develop a new model of insulin-glucose dynamics for forecasting blood...
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12/01/2018
Measuring the Stability of EHR- and EKG-based Predictive Models
Databases of electronic health records (EHRs) are increasingly used to i...
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12/01/2018
A Probabilistic Model of Cardiac Physiology and Electrocardiograms
An electrocardiogram (EKG) is a common, non-invasive test that measures ...
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02/28/2018
Approximate Inference for Constructing Astronomical Catalogs from Images
We present a new, fully generative model for constructing astronomical c...
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02/07/2018
Semi-Amortized Variational Autoencoders
Amortized variational inference (AVI) replaces instance-specific local i...
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05/22/2017
Reducing Reparameterization Gradient Variance
Optimization with noisy gradients has become ubiquitous in statistics an...
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11/20/2016
Variational Boosting: Iteratively Refining Posterior Approximations
We propose a black-box variational inference method to approximate intra...
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10/26/2016