Jacob M. Springer

According to our database, Jacob M. Springer authored at least 8 papers between 2018 and 2022.

Collaborative distances:

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

2022

If you've trained one you've trained them all: inter-architecture similarity increases with robustness.

Haydn T. Jones, Jacob M. Springer, Garrett T. Kenyon, Juston S. Moore

Proceedings of the Uncertainty in Artificial Intelligence, 2022

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

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 Robust Features for Targeted Transfer Attacks.

Jacob M. Springer, Melanie Mitchell, Garrett T. Kenyon

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

It's Hard for Neural Networks to Learn the Game of Life.

Jacob M. Springer, Garrett T. Kenyon

Proceedings of the International Joint Conference on Neural Networks, 2021

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

Sparse MP4.

Daniel A. Wang, Charles M. S. Strauss, Jacob M. Springer, Austin Thresher, Howard Pritchard, Garrett T. Kenyon

Proceedings of the IEEE Southwest Symposium on Image Analysis and Interpretation, 2020

2018

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, Garrett T. Kenyon

CoRR, 2018