Alejandro Schuler

19 papers A* 1C 1Misc 3Journal 13Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Highly Adaptive Principal Component Regression. CoRR Mingxun Wang, Alejandro Schuler, Mark J. van der Laan, Carlos García-Meixide
2025	J	`jnl`	RieszBoost: Gradient Boosting for Riesz Regression. CoRR Kaitlyn J. Lee, Alejandro Schuler
2025	J	`jnl`	Targeted Deep Architectures: A TMLE-Based Framework for Robust Causal Inference in Neural Networks. CoRR Yi Li, David McCoy, Nolan Gunter, Kaitlyn Lee, Alejandro Schuler, Mark J. van der Laan
2024	J	`jnl`	Highly Adaptive Ridge. CoRR Alejandro Schuler, Alexander Hagemeister, Mark J. van der Laan
2023	J	`jnl`	SuperNOVA: Semi-Parametric Identification and Estimation of Interaction and Effect Modification in Mixed Exposures using Stochastic Interventions in R. J. Open Source Softw. David McCoy, Alejandro Schuler, Alan E. Hubbard, Mark J. van der Laan
2022	J	`jnl`	Exploratory analysis of novel electronic health record variables for quantification of healthcare delivery strain, prediction of mortality, and prediction of imminent discharge. J. Am. Medical Informatics Assoc. Catherine Lee, Brian L. Lawson, Ariana J. Mann, Vincent X. Liu, Laura C. Myers, Alejandro Schuler, Gabriel J. Escobar
2022	J	`jnl`	The Selectively Adaptive Lasso. CoRR Alejandro Schuler, Mark J. van der Laan
2021	Misc	`conf`	Integrating Evaluations of Predictive Algorithm-Driven Interventions into Clinical Workflows with the Dynamic Discontinuity Deployment Design. AMIA Ben J. Marafino, Alejandro Schuler, Vincent X. Liu, Art B. Owen, Gabriel J. Escobar, Michael T. M. Baiocchi
2021	J	`jnl`	Multivariate Probabilistic Regression with Natural Gradient Boosting. CoRR Michael O'Malley, Adam M. Sykulski, Rick Lumpkin, Alejandro Schuler
2020	J	`jnl`	Increasing the efficiency of randomized trial estimates via linear adjustment for a prognostic score. CoRR Alejandro Schuler, David Walsh, Diana Hall, Jon Walsh, Charles Fisher
2020	A*	`conf`	NGBoost: Natural Gradient Boosting for Probabilistic Prediction. ICML Tony Duan, Anand Avati, Daisy Yi Ding, Khanh K. Thai, Sanjay Basu, Andrew Y. Ng, Alejandro Schuler
2020	C	`conf`	Operationally-Informed Hospital-Wide Discharge Prediction Using Machine Learning. HealthCom Andrew Ward, Ariana J. Mann, Jacqueline Vallon, Gabriel J. Escobar, Nicholas Bambos, Alejandro Schuler
2020	J	`jnl`	Performance metrics for intervention-triggering prediction models do not reflect an expected reduction in outcomes from using the model. CoRR Alejandro Schuler, Aashish Bhardwaj, Vincent X. Liu
2019	J	`jnl`	NGBoost: Natural Gradient Boosting for Probabilistic Prediction. CoRR Tony Duan, Anand Avati, Daisy Yi Ding, Sanjay Basu, Andrew Y. Ng, Alejandro Schuler
2018	J	`jnl`	An evaluation of clinical order patterns machine-learned from clinician cohorts stratified by patient mortality outcomes. J. Biomed. Informatics Jason K. Wang, Jason Hom, Santhosh Balasubramanian, Alejandro Schuler, Nigam H. Shah, Mary K. Goldstein, Michael T. M. Baiocchi, Jonathan H. Chen
2018	J	`jnl`	General-purpose validation and model selection when estimating individual treatment effects. CoRR Alejandro Schuler, Nigam Shah
2017	—	`conf`	A novel propensity modeling approach to estimate the causal impact of acute organ dysfunction on long-term survival in sepsis. CRI Alejandro Schuler, David A. Wulf, Yun Lu, Jennifer M. Baker, Gabriel J. Escobar, Nigam Shah, Vincent X. Liu
2017	Misc	`conf`	Impact of Clinician Experience on Machine Learned Clinical Order Patterns. AMIA Jason K. Wang, Alejandro Schuler, Nigam Shah, Jonathan H. Chen
2016	Misc	`conf`	Discovering Patient Phenotypes Using Generalized Low Rank Models. PSB Alejandro Schuler, Vincent X. Liu, Joe Wan, Alison Callahan, Madeleine Udell, David E. Stark, Nigam H. Shah