Benjamin J. Lengerich

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 22

Top Topics

Diabetes Mellitus

Dimensional Data

Additive Models

Top Venues

Publications

Tomas M. Bosschieter, Zifei Xu, Hui Lan, Benjamin J. Lengerich, Harsha Nori, Ian S. Painter, Vivienne Souter, Rich Caruana
Interpretable Predictive Models to Understand Risk Factors for Maternal and Fetal Outcomes. J. Heal. Informatics Res. 8 (1) (2024)
Sebastian Bordt, Benjamin J. Lengerich, Harsha Nori, Rich Caruana
Data Science with LLMs and Interpretable Models. CoRR (2024)
Benjamin J. Lengerich, Sebastian Bordt, Harsha Nori, Mark E. Nunnally, Yin Aphinyanaphongs, Manolis Kellis, Rich Caruana
LLMs Understand Glass-Box Models, Discover Surprises, and Suggest Repairs. CoRR (2023)
Benjamin J. Lengerich, Caleb N. Ellington, Andrea Rubbi, Manolis Kellis, Eric P. Xing
Contextualized Machine Learning. CoRR (2023)
Tomas M. Bosschieter, Zifei Xu, Hui Lan, Benjamin J. Lengerich, Harsha Nori, Ian Painter, Vivienne Souter, Rich Caruana
Interpretable Predictive Models to Understand Risk Factors for Maternal and Fetal Outcomes. CoRR (2023)
Jannik Deuschel, Caleb N. Ellington, Benjamin J. Lengerich, Yingtao Luo, Pascal Friederich, Eric P. Xing
Contextualized Policy Recovery: Modeling and Interpreting Medical Decisions with Adaptive Imitation Learning. CoRR (2023)
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
Ten quick tips for deep learning in biology. PLoS Comput. Biol. 18 (3) (2022)
Benjamin J. Lengerich, Mark E. Nunnally, Yin Aphinyanaphongs, Rich Caruana
Estimating Discontinuous Time-Varying Risk Factors and Treatment Benefits for COVID-19 with Interpretable ML. CoRR (2022)
Benjamin J. Lengerich, Eric P. Xing, Rich Caruana
Dropout as a Regularizer of Interaction Effects. AISTATS (2022)
Benjamin J. Lengerich, Mark E. Nunnally, Yin Aphinyanaphongs, Caleb Ellington, Rich Caruana
Automated interpretable discovery of heterogeneous treatment effectiveness: A COVID-19 case study. J. Biomed. Informatics 130 (2022)
Tomas M. Bosschieter, Zifei Xu, Hui Lan, Benjamin J. Lengerich, Harsha Nori, Kristin Sitcov, Vivienne Souter, Rich Caruana
Using Interpretable Machine Learning to Predict Maternal and Fetal Outcomes. CoRR (2022)
Rich Caruana, Benjamin J. Lengerich, Yindalon Aphinyanaphongs
Data-Driven Patterns in Protective Effects of Ibuprofen and Ketorolac on Hospitalized Covid-19 Patients. AMIA (2021)
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
Ten Quick Tips for Deep Learning in Biology. CoRR (2021)
Rishabh Agarwal, Levi Melnick, Nicholas Frosst, Xuezhou Zhang, Benjamin J. Lengerich, Rich Caruana, Geoffrey E. Hinton
Neural Additive Models: Interpretable Machine Learning with Neural Nets. NeurIPS (2021)
Haohan Wang, Benjamin J. Lengerich, Bryon Aragam, Eric P. Xing
Precision Lasso: accounting for correlations and linear dependencies in high-dimensional genomic data. Bioinform. 35 (7) (2019)
Benjamin J. Lengerich, Bryon Aragam, Eric P. Xing
Learning Sample-Specific Models with Low-Rank Personalized Regression. NeurIPS (2019)
Benjamin J. Lengerich, Bryon Aragam, Eric P. Xing
Learning Sample-Specific Models with Low-Rank Personalized Regression. CoRR (2019)
Benjamin J. Lengerich, Bryon Aragam, Eric P. Xing
Personalized regression enables sample-specific pan-cancer analysis. Bioinform. 34 (13) (2018)
Micol Marchetti-Bowick, Benjamin J. Lengerich, Ankur P. Parikh, Eric P. Xing
Hybrid Subspace Learning for High-Dimensional Data. CoRR (2018)
Benjamin J. Lengerich, Andrew L. Maas, Christopher Potts
Retrofitting Distributional Embeddings to Knowledge Graphs with Functional Relations. COLING (2018)
Benjamin J. Lengerich, Sandeep Konam, Eric P. Xing, Stephanie Rosenthal, Manuela M. Veloso
Visual Explanations for Convolutional Neural Networks via Input Resampling. CoRR (2017)
Benjamin J. Lengerich, Andrew L. Maas, Christopher Potts
Retrofitting Distributional Embeddings to Knowledge Graphs with Functional Relations. CoRR (2017)