Matthew Ploenzke

Interpreting Deep Neural Networks Beyond Attribution Methods: Quantifying Global Importance of Genomic Features

Peter K Koo, Matthew Ploenzke, Peter K. Koo, 2020, bioRxiv.

Interpretable Convolution Methods for Learning Genomic Sequence Motifs

Rafael A. Irizarry, Matthew Ploenzke, R. Irizarry, 2018, bioRxiv.

Improving Convolutional Network Interpretability with Exponential Activations

Peter K. Koo, Matthew Ploenzke, 2019 .

Global Importance Analysis: A Method to Quantify Importance of Genomic Features in Deep Neural Networks

Matthew Ploenzke, Steffan B. Paul, Peter K. Koo, 2020, bioRxiv.

SNIP: An Adaptation of Sorted Neighborhood Methods for Deduplicating Pedigree Data

Theodore Huang, Danielle Braun, Matthew Ploenzke, 2021, 2108.08773.