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Jacob M. Springer
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2020 – today
- 2022
- [c4]Haydn T. Jones, Jacob M. Springer, Garrett T. Kenyon, Juston S. Moore:
If you've trained one you've trained them all: inter-architecture similarity increases with robustness. UAI 2022: 928-937 - 2021
- [c3]Jacob M. Springer, Garrett T. Kenyon:
It's Hard for Neural Networks to Learn the Game of Life. IJCNN 2021: 1-8 - [c2]Jacob M. Springer, Melanie Mitchell, Garrett T. Kenyon:
A Little Robustness Goes a Long Way: Leveraging Robust Features for Targeted Transfer Attacks. NeurIPS 2021: 9759-9773 - [i5]Jacob M. Springer, Melanie Mitchell, Garrett T. Kenyon:
Adversarial Perturbations Are Not So Weird: Entanglement of Robust and Non-Robust Features in Neural Network Classifiers. CoRR abs/2102.05110 (2021) - [i4]Jacob M. Springer, Melanie Mitchell, Garrett T. Kenyon:
A Little Robustness Goes a Long Way: Leveraging Universal Features for Targeted Transfer Attacks. CoRR abs/2106.02105 (2021) - 2020
- [c1]Daniel A. Wang, Charles M. S. Strauss, Jacob M. Springer, Austin Thresher, Howard Pritchard, Garrett T. Kenyon:
Sparse MP4. SSIAI 2020: 99-103 - [i3]Jacob M. Springer, Garrett T. Kenyon:
It's Hard for Neural Networks To Learn the Game of Life. CoRR abs/2009.01398 (2020) - [i2]Jacob M. Springer, Bryn Marie Reinstadler, Una-May O'Reilly:
STRATA: Building Robustness with a Simple Method for Generating Black-box Adversarial Attacks for Models of Code. CoRR abs/2009.13562 (2020)
2010 – 2019
- 2018
- [i1]Jacob M. Springer, Charles M. S. Strauss, Austin M. Thresher, Edward Kim, Garrett T. Kenyon:
Classifiers Based on Deep Sparse Coding Architectures are Robust to Deep Learning Transferable Examples. CoRR abs/1811.07211 (2018)
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