A unifying representation for a class of dependent random measures. - Nicholas J. Foti; Joseph D. Futoma; Daniel N. Rockmore; Sinead Williamson (AISTATS, 2013)

A comparison of models for predicting early hospital readmissions. - Joseph Futoma; Jonathan Morris; Joseph Lucas (J. Biomed. Informatics, 2015)

Predicting Disease Progression with a Model for Multivariate Longitudinal Clinical Data. - Joseph Futoma; Mark P. Sendak; Blake Cameron; Katherine A. Heller (MLHC, 2016)

Scalable Joint Modeling of Longitudinal and Point Process Data for Disease Trajectory Prediction and Improving Management of Chronic Kidney Disease. - Joseph Futoma; Mark P. Sendak; Blake Cameron; Katherine A. Heller (UAI, 2016)

Learning to Detect Sepsis with a Multitask Gaussian Process RNN Classifier. - Joseph Futoma; Sanjay Hariharan; Katherine A. Heller (ICML, 2017)

An Improved Multi-Output Gaussian Process RNN with Real-Time Validation for Early Sepsis Detection. - Joseph Futoma; Sanjay Hariharan; Katherine A. Heller; Mark P. Sendak; Nathan Brajer; Meredith Clement; Armando Bedoya; Cara O'Brien (MLHC, 2017)

Gaussian Process-Based Models for Clinical Time Series in Healthcare. - Joseph Futoma (2018)

POPCORN: Partially Observed Prediction Constrained Reinforcement Learning. - Joseph Futoma; Michael C. Hughes; Finale Doshi-Velez (AISTATS, 2020)

"The human body is a black box": supporting clinical decision-making with deep learning. - Mark P. Sendak; Madeleine Clare Elish; Michael Gao; Joseph Futoma; William Ratliff; Marshall Nichols; Armando Bedoya; Suresh Balu; Cara O'Brien (FAT*, 2020)

Interpretable Off-Policy Evaluation in Reinforcement Learning by Highlighting Influential Transitions. - Omer Gottesman; Joseph Futoma; Yao Liu 009; Sonali Parbhoo; Leo A. Celi; Emma Brunskill; Finale Doshi-Velez (ICML, 2020)

Model-based Reinforcement Learning for Semi-Markov Decision Processes with Neural ODEs. - Jianzhun Du; Joseph Futoma; Finale Doshi-Velez (NeurIPS, 2020)

Identifying Distinct, Effective Treatments for Acute Hypotension with SODA-RL: Safely Optimized Diverse Accurate Reinforcement Learning. - Joseph Futoma; Muhammad A. Masood; Finale Doshi-Velez (CoRR, 2020)

Model-based metrics: Sample-efficient estimates of predictive model subpopulation performance. - Andrew C. Miller; Leon A. Gatys; Joseph Futoma; Emily B. Fox (MLHC, 2021)

It's complicated: characterizing the time-varying relationship between cell phone mobility and COVID-19 spread in the US. - Sean Jewell; Joseph Futoma; Lauren Hannah; Andrew C. Miller; Nicholas J. Foti; Emily B. Fox (npj Digit. Medicine, 2021)

Wearable Accelerometer Foundation Models for Health via Knowledge Distillation. - Salar Abbaspourazad; Anshuman Mishra; Joseph Futoma; Andrew C. Miller; Ian Shapiro (CoRR, 2024)

Beyond Sensor Data: Foundation Models of Behavioral Data from Wearables Improve Health Predictions. - Eray Erturk; Fahad Kamran; Salar Abbaspourazad; Sean Jewell; Harsh Sharma; Yujie Li; Sinead Williamson; Nicholas J. Foti; Joseph Futoma (CoRR, 2025)