Estimating the position of illuminants in paintings under weak model assumptions: an application to the works of two Baroque masters. - David C. Kale; David G. Stork (Human Vision and Electronic Imaging, 2009)

An informatics architecture for the Virtual Pediatric Intensive Care Unit. - Daniel J. Crichton; Chris A. Mattmann; Andrew F. Hart; David C. Kale; Robinder G. Khemani; Patrick Ross; Sarah Rubin; Paul Veeravatanayothin; Amy Braverman; Cameron Goodale; Randall C. Wetzel (CBMS, 2011)

Sim•TwentyFive: An Interactive Visualization System for Data-Driven Decision Support. - Brendan Stubbs; David C. Kale (AMIA, 2012)

Unsupervised pattern discovery in electronic health care data using probabilistic clustering models. - Benjamin M. Marlin; David C. Kale; Robinder G. Khemani; Randall C. Wetzel (IHI, 2012)

Capturing Data Analytics Expertise with Visualizations in Workflows. - David C. Kale; Samuel Di; Yan Liu 002; Yolanda Gil (AAAI Fall Symposia, 2013)

Accelerating Active Learning with Transfer Learning. - David C. Kale; Yan Liu (ICDM, 2013)

Preface. - Finale Doshi-Velez; David C. Kale; Byron C. Wallace; Jenna Wiens (AAAI Workshop: Modern Artificial Intelligence for Health Analytics, 2014)

An Examination of Multivariate Time Series Hashing with Applications to Health Care. - David C. Kale; Dian Gong; Zhengping Che; Yan Liu 002; Gérard G. Medioni; Randall C. Wetzel; Patrick Ross (ICDM, 2014)

Causal Phenotype Discovery via Deep Networks. - David C. Kale; Zhengping Che; Mohammad Taha Bahadori; Wenzhe Li; Yan Liu 002; Randall C. Wetzel (AMIA, 2015)

Functional Subspace Clustering with Application to Time Series. - Mohammad Taha Bahadori; David C. Kale; Yingying Fan; Yan Liu 002 (ICML, 2015)

Deep Computational Phenotyping. - Zhengping Che; David C. Kale; Wenzhe Li; Mohammad Taha Bahadori; Yan Liu 002 (KDD, 2015)

Hierarchical Active Transfer Learning. - David C. Kale; Marjan Ghazvininejad; Anil Ramakrishna; Jingrui He; Yan Liu 002 (SDM, 2015)

Phenotyping of Clinical Time Series with LSTM Recurrent Neural Networks. - Zachary Chase Lipton; David C. Kale; Randall C. Wetzel (CoRR, 2015)

Learning and Optimization with Submodular Functions. - Bharath Sankaran; Marjan Ghazvininejad; Xinran He; David C. Kale; Liron Cohen 002 (CoRR, 2015)

Directly Modeling Missing Data in Sequences with RNNs: Improved Classification of Clinical Time Series. - Zachary C. Lipton; David C. Kale; Randall C. Wetzel (MLHC, 2016)

Learning to Diagnose with LSTM Recurrent Neural Networks. - Zachary Chase Lipton; David C. Kale; Charles Elkan; Randall C. Wetzel (ICLR (Poster), 2016)

Intra-day Activity Better Predicts Chronic Conditions. - Tom Quisel; David C. Kale; Luca Foschini 002 (CoRR, 2016)

Toward Interpretable Topic Discovery via Anchored Correlation Explanation. - Kyle Reing; David C. Kale; Greg Ver Steeg; Aram Galstyan (CoRR, 2016)

Time Series Feature Learning with Applications to Health Care. - Zhengping Che; Sanjay Purushotham; David C. Kale; Wenzhe Li; Mohammad Taha Bahadori; Robinder G. Khemani; Yan Liu 002 (Mobile Health - Sensors, Analytic Methods, and Applications, 2017)

The Effectiveness of Transfer Learning in Electronic Health Records Data. - Sébastien Dubois; Nathanael Romano; Kenneth Jung; Nigam Shah; David C. Kale (ICLR (Workshop), 2017)

Collecting and Analyzing Millions of mHealth Data Streams. - Tom Quisel; Luca Foschini 001; Alessio Signorini; David C. Kale (KDD, 2017)

Multitask Learning and Benchmarking with Clinical Time Series Data. - Hrayr Harutyunyan; Hrant Khachatrian; David C. Kale; Aram Galstyan (CoRR, 2017)

Anchored Correlation Explanation: Topic Modeling with Minimal Domain Knowledge. - Ryan J. Gallagher; Kyle Reing; David C. Kale; Greg Ver Steeg (Trans. Assoc. Comput. Linguistics, 2017)

The Effectiveness of Multitask Learning for Phenotyping with Electronic Health Records Data. - Daisy Yi Ding; Chloé Simpson; Stephen Pfohl; Dave C. Kale; Kenneth Jung; Nigam H. Shah (PSB, 2019)