Classifiers Based on Deep Sparse Coding Architectures are Robust to Deep Learning Transferable Examples. - Jacob M. Springer; Charles M. S. Strauss; Austin M. Thresher; Edward Kim 006; Garrett T. Kenyon (CoRR, 2018)

Sparse MP4. - Daniel A. Wang; Charles M. S. Strauss; Jacob M. Springer; Austin Thresher; Howard Pritchard; Garrett T. Kenyon (SSIAI, 2020)

STRATA: Building Robustness with a Simple Method for Generating Black-box Adversarial Attacks for Models of Code. - Jacob M. Springer; Bryn Marie Reinstadler; Una-May O'Reilly (CoRR, 2020)

It's Hard for Neural Networks to Learn the Game of Life. - Jacob M. Springer; Garrett T. Kenyon (IJCNN, 2021)

A Little Robustness Goes a Long Way: Leveraging Robust Features for Targeted Transfer Attacks. - Jacob M. Springer; Melanie Mitchell; Garrett T. Kenyon (NeurIPS, 2021)

Adversarial Perturbations Are Not So Weird: Entanglement of Robust and Non-Robust Features in Neural Network Classifiers. - Jacob M. Springer; Melanie Mitchell; Garrett T. Kenyon (CoRR, 2021)

A Little Robustness Goes a Long Way: Leveraging Universal Features for Targeted Transfer Attacks. - Jacob M. Springer; Melanie Mitchell; Garrett T. Kenyon (CoRR, 2021)

If you've trained one you've trained them all: inter-architecture similarity increases with robustness. - Haydn Thomas Jones; Jacob M. Springer; Garrett T. Kenyon; Juston S. Moore (UAI, 2022)