Ensembled sparse-input hierarchical networks for high-dimensional datasets
Feng and Simon

Sparse-Input Neural Networks for High-dimensional Nonparametric Regression and Classification
Feng and Simon

Bayesian logistic regression for online recalibration and revision of risk prediction models with performance guarantees
Feng, Gossmann, Sahiner and Pirracchio

In press

Selective prediction-set models with coverage guarantees
Feng, Sondhi, Perry and Simon
Biometrics, In press


Estimation of cell lineage trees by maximum-likelihood phylogenetics
Feng, DeWitt, McKenna, Simon, Willis and Matsen
Annals of Applied Statistics, 2021

Learning to safely approve updates to machine learning algorithms
Proceedings of the Conference on Health, Inference, and Learning, 2021


Efficient nonparametric statistical inference on population feature importance using Shapley values
Williamson and Feng
International Conference on Machine Learning (ICML), 2020

An analysis of the cost of hyper-parameter selection via split-sample validation, with applications to penalized regression
Feng and Simon
Statistica Sinica, 2020

Approval policies for modifications to Machine Learning-Based Software as a Medical Device: A study of bio-creep
Feng, Emerson and Simon
Biometrics, 2020


Deep generative models for T cell receptor protein sequences
Davidsen, Olson, DeWitt, Feng, Harkins, Bradley and Matsen
Elife, 2019

Survival analysis of DNA mutation motifs with penalized proportional hazards
Feng, Shaw, Minin, Simon and Matsen
Ann. Appl. Stat., 2019


Gradient-based Regularization Parameter Selection for Problems With Nonsmooth Penalty Functions
Feng and Simon
J. Comput. Graph. Stat., 2018

Nonparametric variable importance using an augmented neural network with multi-task learning
Feng, Williamson, Simon and Carone
International Conference on Machine Learning (ICML), 2018