Publications

Found 6 results
Author Title Type [ Year(Asc)]
Filters: Author is N. Benjamin Erichson  [Clear All Filters]
2022
N. Erichson, B., Lim S. Hoe, Utrera F., Xu W., Cao Z., & Mahoney M. (2022).  NoisyMix: Boosting Robustness by Combining Data Augmentations, Stability Training, and Noise Injections. arXiv.
2021
Utrera, F., Kravitz E., N. Erichson B., Khanna R., & Mahoney M. (2021).  Adversarially-Trained Deep Nets Transfer Better: Illustration on Image Classification. International Conference on Learning Representations.
N. Erichson, B., Azencot O., Queiruga A., Hodgkinson L., & Mahoney M. (2021).  Lipschitz recurrent neural networks. International Conference on Learning Representations.
N. Erichson, B., Taylor D., Wu Q., & Mahoney M. (2021).  Noise-Response Analysis of Deep Neural Networks Quantifies Robustness and Fingerprints Structural Malware. Proceedings of the 2021 SIAM International Conference on Data Mining (SDM). 100-108.
Lim, S. Hoe, N. Erichson B., Hodgkinson L., & Mahoney M. (2021).  Noisy Recurrent Neural Networks. Advances in Neural Information Processing Systems Conference. 34,
2020
N. Erichson, B., Mathelin L., Yao Z., Bruntonq S. L., Mahoney M., & J. Kutz N. (2020).  Shallow neural networks for fluid flow reconstruction with limited sensors. Proceedings of the Royal Society A. 476(2238),