Benjamin J. Lengerich

34 papers A* 4A 2B 1Misc 1Journal 25

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	The hidden risk of round numbers and sharp thresholds in clinical practice. npj Digit. Medicine Benjamin J. Lengerich, Rich Caruana, Mark E. Nunnally, Manolis Kellis
2024	A*	`conf`	Contextualized Policy Recovery: Modeling and Interpreting Medical Decisions with Adaptive Imitation Learning. ICML Jannik Deuschel, Caleb Ellington, Yingtao Luo, Benjamin J. Lengerich, Pascal Friederich, Eric P. Xing
2024	J	`jnl`	Contextualized: Heterogeneous Modeling Toolbox. J. Open Source Softw. Caleb N. Ellington, Benjamin J. Lengerich, Wesley Lo, Aaron Alvarez, Andrea Rubbi, Manolis Kellis, Eric P. Xing
2024	J	`jnl`	Data Science with LLMs and Interpretable Models. CoRR Sebastian Bordt, Benjamin J. Lengerich, Harsha Nori, Rich Caruana
2024	J	`jnl`	Interpretable Predictive Models to Understand Risk Factors for Maternal and Fetal Outcomes. J. Heal. Informatics Res. Tomas M. Bosschieter, Zifei Xu, Hui Lan, Benjamin J. Lengerich, Harsha Nori, Ian S. Painter, Vivienne Souter, Rich Caruana
2024	J	`jnl`	Patient-Specific Models of Treatment Effects Explain Heterogeneity in Tuberculosis. CoRR Ethan Wu, Caleb Ellington, Benjamin J. Lengerich, Eric P. Xing
2023	J	`jnl`	Contextualized Machine Learning. CoRR Benjamin J. Lengerich, Caleb N. Ellington, Andrea Rubbi, Manolis Kellis, Eric P. Xing
2023	J	`jnl`	Contextualized Policy Recovery: Modeling and Interpreting Medical Decisions with Adaptive Imitation Learning. CoRR Jannik Deuschel, Caleb N. Ellington, Benjamin J. Lengerich, Yingtao Luo, Pascal Friederich, Eric P. Xing
2023	J	`jnl`	Interpretable Predictive Models to Understand Risk Factors for Maternal and Fetal Outcomes. CoRR Tomas M. Bosschieter, Zifei Xu, Hui Lan, Benjamin J. Lengerich, Harsha Nori, Ian S. Painter, Vivienne Souter, Rich Caruana
2023	J	`jnl`	LLMs Understand Glass-Box Models, Discover Surprises, and Suggest Repairs. CoRR Benjamin J. Lengerich, Sebastian Bordt, Harsha Nori, Mark E. Nunnally, Yin Aphinyanaphongs, Manolis Kellis, Rich Caruana
2022	J	`jnl`	Automated interpretable discovery of heterogeneous treatment effectiveness: A COVID-19 case study. J. Biomed. Informatics Benjamin J. Lengerich, Mark E. Nunnally, Yin Aphinyanaphongs, Caleb Ellington, Rich Caruana
2022	A	`conf`	Dropout as a Regularizer of Interaction Effects. AISTATS Benjamin J. Lengerich, Eric P. Xing, Rich Caruana
2022	J	`jnl`	Estimating Discontinuous Time-Varying Risk Factors and Treatment Benefits for COVID-19 with Interpretable ML. CoRR Benjamin J. Lengerich, Mark E. Nunnally, Yin Aphinyanaphongs, Rich Caruana
2022	J	`jnl`	Executive Function: A Contrastive Value Policy for Resampling and Relabeling Perceptions via Hindsight Summarization? CoRR Chris Lengerich, Benjamin J. Lengerich
2022	J	`jnl`	Ten quick tips for deep learning in biology. PLoS Comput. Biol. Benjamin D. Lee, Anthony Gitter, Casey S. Greene, Sebastian Raschka, Finlay Maguire, Alexander J. Titus, Michael D. Kessler, Alexandra J. Lee, Marc G. Chevrette, Paul Allen Stewart, Thiago Britto-Borges, Evan M. Cofer, Kun-Hsing Yu, Juan Jose Carmona, Elana J. Fertig, Alexandr A. Kalinin, Brandon Signal, Benjamin J. Lengerich, Timothy J. Triche Jr., Simina M. Boca
2022	J	`jnl`	Using Interpretable Machine Learning to Predict Maternal and Fetal Outcomes. CoRR Tomas M. Bosschieter, Zifei Xu, Hui Lan, Benjamin J. Lengerich, Harsha Nori, Kristin Sitcov, Vivienne Souter, Rich Caruana
2021	Misc	`conf`	Data-Driven Patterns in Protective Effects of Ibuprofen and Ketorolac on Hospitalized Covid-19 Patients. AMIA Rich Caruana, Benjamin J. Lengerich, Yindalon Aphinyanaphongs
2021	A*	`conf`	How Interpretable and Trustworthy are GAMs? KDD Chun-Hao Chang, Sarah Tan, Benjamin J. Lengerich, Anna Goldenberg, Rich Caruana
2021	J	`jnl`	NOTMAD: Estimating Bayesian Networks with Sample-Specific Structures and Parameters. CoRR Benjamin J. Lengerich, Caleb Ellington, Bryon Aragam, Eric P. Xing, Manolis Kellis
2021	A*	`conf`	Neural Additive Models: Interpretable Machine Learning with Neural Nets. NeurIPS Rishabh Agarwal, Levi Melnick, Nicholas Frosst, Xuezhou Zhang, Benjamin J. Lengerich, Rich Caruana, Geoffrey E. Hinton
2021	—	`—`	Sample-Specific Models for Precision Medicine. Benjamin J. Lengerich
2021	J	`jnl`	Ten Quick Tips for Deep Learning in Biology. CoRR Benjamin D. Lee, Anthony Gitter, Casey S. Greene, Sebastian Raschka, Finlay Maguire, Alexander J. Titus, Michael D. Kessler, Alexandra J. Lee, Marc G. Chevrette, Paul Allen Stewart, Thiago Britto-Borges, Evan M. Cofer, Kun-Hsing Yu, Juan Jose Carmona, Elana J. Fertig, Alexandr A. Kalinin, Beth Signal, Benjamin J. Lengerich, Timothy J. Triche Jr., Simina M. Boca
2020	J	`jnl`	How Interpretable and Trustworthy are GAMs? CoRR Chun-Hao Chang, Sarah Tan, Benjamin J. Lengerich, Anna Goldenberg, Rich Caruana
2020	J	`jnl`	On Dropout, Overfitting, and Interaction Effects in Deep Neural Networks. CoRR Benjamin J. Lengerich, Eric P. Xing, Rich Caruana
2020	A	`conf`	Purifying Interaction Effects with the Functional ANOVA: An Efficient Algorithm for Recovering Identifiable Additive Models. AISTATS Benjamin J. Lengerich, Sarah Tan, Chun-Hao Chang, Giles Hooker, Rich Caruana
2019	A*	`conf`	Learning Sample-Specific Models with Low-Rank Personalized Regression. NeurIPS Benjamin J. Lengerich, Bryon Aragam, Eric P. Xing
2019	J	`jnl`	Learning Sample-Specific Models with Low-Rank Personalized Regression. CoRR Benjamin J. Lengerich, Bryon Aragam, Eric P. Xing
2019	J	`jnl`	Precision Lasso: accounting for correlations and linear dependencies in high-dimensional genomic data. Bioinform. Haohan Wang, Benjamin J. Lengerich, Bryon Aragam, Eric P. Xing
2019	J	`jnl`	Purifying Interaction Effects with the Functional ANOVA: An Efficient Algorithm for Recovering Identifiable Additive Models. CoRR Benjamin J. Lengerich, Sarah Tan, Chun-Hao Chang, Giles Hooker, Rich Caruana
2018	J	`jnl`	Hybrid Subspace Learning for High-Dimensional Data. CoRR Micol Marchetti-Bowick, Benjamin J. Lengerich, Ankur P. Parikh, Eric P. Xing
2018	J	`jnl`	Personalized regression enables sample-specific pan-cancer analysis. Bioinform. Benjamin J. Lengerich, Bryon Aragam, Eric P. Xing
2018	B	`conf`	Retrofitting Distributional Embeddings to Knowledge Graphs with Functional Relations. COLING Benjamin J. Lengerich, Andrew L. Maas, Christopher Potts
2017	J	`jnl`	Retrofitting Distributional Embeddings to Knowledge Graphs with Functional Relations. CoRR Benjamin J. Lengerich, Andrew L. Maas, Christopher Potts
2017	J	`jnl`	Visual Explanations for Convolutional Neural Networks via Input Resampling. CoRR Benjamin J. Lengerich, Sandeep Konam, Eric P. Xing, Stephanie Rosenthal, Manuela M. Veloso