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Model-based Reinforcement Learning for Semi-Markov Decision Processes with Neural ODEs
We present two elegant solutions for modeling continuous-time dynamics, ...
06/29/2020 ∙ by Jianzhun Du, et al. ∙
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Interpretable Off-Policy Evaluation in Reinforcement Learning by Highlighting Influential Transitions
Off-policy evaluation in reinforcement learning offers the chance of usi...
02/10/2020 ∙ by Omer Gottesman, et al. ∙
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POPCORN: Partially Observed Prediction COnstrained ReiNforcement Learning
Many medical decision-making settings can be framed as partially observe...
01/13/2020 ∙ by Joseph Futoma, et al. ∙
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Identifying Distinct, Effective Treatments for Acute Hypotension with SODA-RL: Safely Optimized Diverse Accurate Reinforcement Learning
Hypotension in critical care settings is a life-threatening emergency th...
01/09/2020 ∙ by Joseph Futoma, et al. ∙
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"The Human Body is a Black Box": Supporting Clinical Decision-Making with Deep Learning
Machine learning technologies are increasingly developed for use in heal...
11/19/2019 ∙ by Mark Sendak, et al. ∙
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An Improved Multi-Output Gaussian Process RNN with Real-Time Validation for Early Sepsis Detection
Sepsis is a poorly understood and potentially life-threatening complicat...
08/19/2017 ∙ by Joseph Futoma, et al. ∙
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Learning to Detect Sepsis with a Multitask Gaussian Process RNN Classifier
We present a scalable end-to-end classifier that uses streaming physiolo...
06/13/2017 ∙ by Joseph Futoma, et al. ∙
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Scalable Modeling of Multivariate Longitudinal Data for Prediction of Chronic Kidney Disease Progression
Prediction of the future trajectory of a disease is an important challen...
08/16/2016 ∙ by Joseph Futoma, et al. ∙
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