David C. Benkeser

According to our database, David C. Benkeser authored at least 8 papers between 2016 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Highly adaptive regression trees.

Sohail Nizam, David C. Benkeser

Evol. Intell., 2024

2022

Accounting for motion in resting-state fMRI: What part of the spectrum are we characterizing in autism spectrum disorder?

Mary Beth Nebel, Daniel E. Lidstone, Liwei Wang, David C. Benkeser, Stewart H. Mostofsky, Benjamin B. Risk

NeuroImage, 2022

'haldensify': Highly adaptive lasso conditional density estimation in 'R'.

Nima S. Hejazi, Mark J. van der Laan, David C. Benkeser

J. Open Source Softw., 2022

A Huber loss-based super learner with applications to healthcare expenditures.

Ziyue Wu, David C. Benkeser

CoRR, 2022

2021

Super LeArner Prediction of NAb Panels (SLAPNAP): a containerized tool for predicting combination monoclonal broadly neutralizing antibody sensitivity.

Brian D. Williamson, Craig A. Magaret, Peter B. Gilbert, Sohail Nizam, Courtney Simmons, David C. Benkeser

Bioinform., November, 2021

2020

txshift: Efficient estimation of the causal effects of stochastic interventions in R.

Nima S. Hejazi, David C. Benkeser

J. Open Source Softw., 2020

2019

Prediction of VRC01 neutralization sensitivity by HIV-1 gp160 sequence features.

Craig A. Magaret, David C. Benkeser, Brian D. Williamson, Bhavesh Borate, Lindsay N. Carpp, Ivelin S. Georgiev, Ian Setliff, Adam S. Dingens, Noah Simon, Marco Carone, Christopher Simpkins, David C. Montefiori, Galit Alter, Wen-Han Yu, Michal Juraska, Paul Thatcher Edlefsen, Shelly Karuna, Nyaradzo M. Mgodi, Srilatha Edugupanti, Peter B. Gilbert

PLoS Comput. Biol., 2019

2016

The Highly Adaptive Lasso Estimator.

David C. Benkeser, Mark J. van der Laan

Proceedings of the 2016 IEEE International Conference on Data Science and Advanced Analytics, 2016