430 citations · 995 across the 30 of their papers we have counts for
9 papers · 1 filter
Variational Refinement for Importance Sampling Using the Forward Kullback-Leibler Divergence
Ghassen Jerfel, Serena Wang, Clara Fannjiang +3
Variational Inference (VI) is a popular alternative to asymptotically exact sampling in Bayesian inference. Its main workhorse is optimization over a reverse Kullback-Leibler diver…
An Improved Multi-Output Gaussian Process RNN with Real-Time Validation for Early Sepsis Detection
Joseph Futoma, Sanjay Hariharan, Mark Sendak +5
Sepsis is a poorly understood and potentially life-threatening complication that can occur as a result of infection. Early detection and treatment improves patient outcomes, and as…
Learning to Detect Sepsis with a Multitask Gaussian Process RNN Classifier
Joseph Futoma, Sanjay Hariharan, Katherine Heller
We present a scalable end-to-end classifier that uses streaming physiological and medication data to accurately predict the onset of sepsis, a life-threatening complication from in…
Transfer Learning via Latent Factor Modeling to Improve Prediction of Surgical Complications
Elizabeth C Lorenzi, Zhifei Sun, Erich Huang +2
We aim to create a framework for transfer learning using latent factor models to learn the dependence structure between a larger source dataset and a target dataset. The methodolog…
Scalable Modeling of Multivariate Longitudinal Data for Prediction of Chronic Kidney Disease Progression
Joseph Futoma, Mark Sendak, C. Blake Cameron +1
Prediction of the future trajectory of a disease is an important challenge for personalized medicine and population health management. However, many complex chronic diseases exhibi…
-means: Fighting against Degeneracy in Sequential Monte Carlo with an Application to Tracking
Kai Fan, Katherine Heller
For regular particle filter algorithm or Sequential Monte Carlo (SMC) methods, the initial weights are traditionally dependent on the proposed distribution, the posterior distribut…