Joseph Futoma
Orcid: 0000-0003-2744-232XAffiliations:
- Apple, New York, NY, USA
- Harvard University, Paulson School of Engineering and Applied Sciences, Cambridge, MA, USA (former)
- Duke University, Department of Statistical Science, Durham, NC, USA (former, PhD 2018)
- Dartmouth College, Department of Mathematics, Hanover, NH, USA (former)
According to our database1,
Joseph Futoma
authored at least 14 papers
between 2013 and 2021.
Collaborative distances:
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Timeline
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Bibliography
2021
It's complicated: characterizing the time-varying relationship between cell phone mobility and COVID-19 spread in the US.
npj Digit. Medicine, 2021
Model-based metrics: Sample-efficient estimates of predictive model subpopulation performance.
Proceedings of the Machine Learning for Healthcare Conference, 2021
2020
Identifying Distinct, Effective Treatments for Acute Hypotension with SODA-RL: Safely Optimized Diverse Accurate Reinforcement Learning.
CoRR, 2020
Model-based Reinforcement Learning for Semi-Markov Decision Processes with Neural ODEs.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Interpretable Off-Policy Evaluation in Reinforcement Learning by Highlighting Influential Transitions.
Proceedings of the 37th International Conference on Machine Learning, 2020
"The human body is a black box": supporting clinical decision-making with deep learning.
Proceedings of the FAT* '20: Conference on Fairness, 2020
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020
2018
PhD thesis, 2018
2017
An Improved Multi-Output Gaussian Process RNN with Real-Time Validation for Early Sepsis Detection.
Proceedings of the Machine Learning for Health Care Conference, 2017
Proceedings of the 34th International Conference on Machine Learning, 2017
2016
Scalable Joint Modeling of Longitudinal and Point Process Data for Disease Trajectory Prediction and Improving Management of Chronic Kidney Disease.
Proceedings of the Thirty-Second Conference on Uncertainty in Artificial Intelligence, 2016
Predicting Disease Progression with a Model for Multivariate Longitudinal Clinical Data.
Proceedings of the 1st Machine Learning in Health Care, 2016
2015
J. Biomed. Informatics, 2015
2013
Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, 2013