N. Benjamin Erichson

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 58

Top Topics

Background Modeling

Error Estimation

Tensor Decomposition

Top Venues

Publications

Annan Yu, Michael W. Mahoney, N. Benjamin Erichson
There is HOPE to Avoid HiPPOs for Long-memory State Space Models. CoRR (2024)
Pu Ren, Rie Nakata, Maxime Lacour, Ilan Naiman, Nori Nakata, Jialin Song, Zhengfa Bi, Osman Asif Malik, Dmitriy Morozov, Omri Azencot, N. Benjamin Erichson, Michael W. Mahoney
Learning Physics for Unveiling Hidden Earthquake Ground Motions via Conditional Generative Modeling. CoRR (2024)
Annan Yu, Arnur Nigmetov, Dmitriy Morozov, Michael W. Mahoney, N. Benjamin Erichson
Robustifying State-space Models for Long Sequences via Approximate Diagonalization. ICLR (2024)
Dongwei Lyu, Rie Nakata, Pu Ren, Michael W. Mahoney, Arben Pitarka, Nori Nakata, N. Benjamin Erichson
WaveCastNet: An AI-enabled Wavefield Forecasting Framework for Earthquake Early Warning. CoRR (2024)
N. Benjamin Erichson, Soon Hoe Lim, Winnie Xu, Francisco Utrera, Ziang Cao, Michael W. Mahoney
NoisyMix: Boosting Model Robustness to Common Corruptions. AISTATS (2024)
Ilan Naiman, N. Benjamin Erichson, Pu Ren, Michael W. Mahoney, Omri Azencot
Generative Modeling of Regular and Irregular Time Series Data via Koopman VAEs. ICLR (2024)
Pu Ren, N. Benjamin Erichson, Shashank Subramanian, Omer San, Zarija Lukic, Michael W. Mahoney
SuperBench: A Super-Resolution Benchmark Dataset for Scientific Machine Learning. CoRR (2023)
Riley Murray, James Demmel, Michael W. Mahoney, N. Benjamin Erichson, Maksim Melnichenko, Osman Asif Malik, Laura Grigori, Piotr Luszczek, Michal Derezinski, Miles E. Lopes, Tianyu Liang, Hengrui Luo, Jack J. Dongarra
Randomized Numerical Linear Algebra : A Perspective on the Field With an Eye to Software. CoRR (2023)
Junwen Yao, N. Benjamin Erichson, Miles E. Lopes
Error Estimation for Random Fourier Features. CoRR (2023)
Annan Yu, Arnur Nigmetov, Dmitriy Morozov, Michael W. Mahoney, N. Benjamin Erichson
Robustifying State-space Models for Long Sequences via Approximate Diagonalization. CoRR (2023)
Ilan Naiman, N. Benjamin Erichson, Pu Ren, Michael W. Mahoney, Omri Azencot
Generative Modeling of Regular and Irregular Time Series Data via Koopman VAEs. CoRR (2023)
Junwen Yao, N. Benjamin Erichson, Miles E. Lopes
Error Estimation for Random Fourier Features. AISTATS (2023)
T. Konstantin Rusch, Siddhartha Mishra, N. Benjamin Erichson, Michael W. Mahoney
Long Expressive Memory for Sequence Modeling. ICLR (2022)
N. Benjamin Erichson, Soon Hoe Lim, Michael W. Mahoney
Gated Recurrent Neural Networks with Weighted Time-Delay Feedback. CoRR (2022)
Soon Hoe Lim, N. Benjamin Erichson, Francisco Utrera, Winnie Xu, Michael W. Mahoney
Noisy Feature Mixup. ICLR (2022)
N. Benjamin Erichson, Soon Hoe Lim, Francisco Utrera, Winnie Xu, Ziang Cao, Michael W. Mahoney
NoisyMix: Boosting Robustness by Combining Data Augmentations, Stability Training, and Noise Injections. CoRR (2022)
Aditi S. Krishnapriyan, Alejandro F. Queiruga, N. Benjamin Erichson, Michael W. Mahoney
Learning continuous models for continuous physics. CoRR (2022)
Soon Hoe Lim, N. Benjamin Erichson, Liam Hodgkinson, Michael W. Mahoney
Noisy Recurrent Neural Networks. CoRR (2021)
Soon Hoe Lim, N. Benjamin Erichson, Francisco Utrera, Winnie Xu, Michael W. Mahoney
Noisy Feature Mixup. CoRR (2021)
Francisco Utrera, Evan Kravitz, N. Benjamin Erichson, Rajiv Khanna, Michael W. Mahoney
Adversarially-Trained Deep Nets Transfer Better: Illustration on Image Classification. ICLR (2021)
Alejandro Queiruga, N. Benjamin Erichson, Liam Hodgkinson, Michael W. Mahoney
Compressing Deep ODE-Nets using Basis Function Expansions. CoRR (2021)
Reese Pathak, Rajat Sen, Nikhil Rao, N. Benjamin Erichson, Michael I. Jordan, Inderjit S. Dhillon
Cluster-and-Conquer: A Framework For Time-Series Forecasting. CoRR (2021)
Soon Hoe Lim, N. Benjamin Erichson, Liam Hodgkinson, Michael W. Mahoney
Noisy Recurrent Neural Networks. NeurIPS (2021)
Alejandro Queiruga, N. Benjamin Erichson, Liam Hodgkinson, Michael W. Mahoney
Stateful ODE-Nets using Basis Function Expansions. NeurIPS (2021)
T. Konstantin Rusch, Siddhartha Mishra, N. Benjamin Erichson, Michael W. Mahoney
Long Expressive Memory for Sequence Modeling. CoRR (2021)
N. Benjamin Erichson, Dane Taylor, Qixuan Wu, Michael W. Mahoney
Noise-Response Analysis of Deep Neural Networks Quantifies Robustness and Fingerprints Structural Malware. SDM (2021)
N. Benjamin Erichson, Omri Azencot, Alejandro Queiruga, Liam Hodgkinson, Michael W. Mahoney
Lipschitz Recurrent Neural Networks. ICLR (2021)
Omri Azencot, N. Benjamin Erichson, Mirela Ben-Chen, Michael W. Mahoney
A Differential Geometry Perspective on Orthogonal Recurrent Models. CoRR (2021)
Miles E. Lopes, N. Benjamin Erichson, Michael W. Mahoney
Error Estimation for Sketched SVD via the Bootstrap. ICML (2020)
N. Benjamin Erichson, Dane Taylor, Qixuan Wu, Michael W. Mahoney
Noise-response Analysis for Rapid Detection of Backdoors in Deep Neural Networks. CoRR (2020)
N. Benjamin Erichson, Peng Zheng, Krithika Manohar, Steven L. Brunton, J. Nathan Kutz, Aleksandr Y. Aravkin
Sparse Principal Component Analysis via Variable Projection. SIAM J. Appl. Math. 80 (2) (2020)
Omri Azencot, N. Benjamin Erichson, Vanessa Lin, Michael W. Mahoney
Forecasting Sequential Data Using Consistent Koopman Autoencoders. ICML (2020)
Alejandro F. Queiruga, N. Benjamin Erichson, Dane Taylor, Michael W. Mahoney
Continuous-in-Depth Neural Networks. CoRR (2020)
Francisco Utrera, Evan Kravitz, N. Benjamin Erichson, Rajiv Khanna, Michael W. Mahoney
Adversarially-Trained Deep Nets Transfer Better. CoRR (2020)
N. Benjamin Erichson, Krithika Manohar, Steven L. Brunton, J. Nathan Kutz
Randomized CP tensor decomposition. Mach. Learn. Sci. Technol. 1 (2) (2020)
Miles E. Lopes, N. Benjamin Erichson, Michael W. Mahoney
Error Estimation for Sketched SVD via the Bootstrap. CoRR (2020)
N. Benjamin Erichson, Zhewei Yao, Michael W. Mahoney
JumpReLU: A Retrofit Defense Strategy for Adversarial Attacks. ICPRAM (2020)
Omri Azencot, N. Benjamin Erichson, Vanessa Lin, Michael W. Mahoney
Forecasting Sequential Data using Consistent Koopman Autoencoders. CoRR (2020)
N. Benjamin Erichson, Omri Azencot, Alejandro Queiruga, Michael W. Mahoney
Lipschitz Recurrent Neural Networks. CoRR (2020)
N. Benjamin Erichson, Lionel Mathelin, Zhewei Yao, Steven L. Brunton, Michael W. Mahoney, J. Nathan Kutz
Shallow Learning for Fluid Flow Reconstruction with Limited Sensors and Limited Data. CoRR (2019)
Zhe Bai, N. Benjamin Erichson, Muralikrishnan Gopalakrishnan Meena, Kunihiko Taira, Steven L. Brunton
Randomized methods to characterize large-scale vortical flow network. CoRR (2019)
N. Benjamin Erichson, Zhewei Yao, Michael W. Mahoney
JumpReLU: A Retrofit Defense Strategy for Adversarial Attacks. CoRR (2019)
Miles E. Lopes, N. Benjamin Erichson, Michael W. Mahoney
Bootstrapping the Operator Norm in High Dimensions: Error Estimation for Covariance Matrices and Sketching. CoRR (2019)
N. Benjamin Erichson, Michael Muehlebach, Michael W. Mahoney
Physics-informed Autoencoders for Lyapunov-stable Fluid Flow Prediction. CoRR (2019)
N. Benjamin Erichson, Lionel Mathelin, J. Nathan Kutz, Steven L. Brunton
Randomized Dynamic Mode Decomposition. SIAM J. Appl. Dyn. Syst. 18 (4) (2019)
N. Benjamin Erichson, Steven L. Brunton, J. Nathan Kutz
Compressed dynamic mode decomposition for background modeling. J. Real Time Image Process. 16 (5) (2019)
Chen Gong, N. Benjamin Erichson, John P. Kelly, Laura C. Trutoiu, Brian T. Schowengerdt, Steven L. Brunton, Eric J. Seibel
RetinaMatch: Efficient Template Matching of Retina Images for Teleophthalmology. IEEE Trans. Medical Imaging 38 (8) (2019)
Chen Gong, N. Benjamin Erichson, John P. Kelly, Laura C. Trutoiu, Brian T. Schowengerdt, Steven L. Brunton, Eric J. Seibel
RetinaMatch: Efficient Template Matching of Retina Images for Teleophthalmology. CoRR (2018)
N. Benjamin Erichson, Lionel Mathelin, Steven L. Brunton, J. Nathan Kutz
Diffusion Maps meet Nyström. CoRR (2018)
N. Benjamin Erichson, Peng Zeng, Krithika Manohar, Steven L. Brunton, J. Nathan Kutz, Aleksandr Y. Aravkin
Sparse Principal Component Analysis via Variable Projection. CoRR (2018)
N. Benjamin Erichson, Ariana Mendible, Sophie Wihlborn, J. Nathan Kutz
Randomized nonnegative matrix factorization. Pattern Recognit. Lett. 104 (2018)
N. Benjamin Erichson, Krithika Manohar, Steven L. Brunton, J. Nathan Kutz
Randomized CP Tensor Decomposition. CoRR (2017)
N. Benjamin Erichson, Steven L. Brunton, J. Nathan Kutz
Compressed Singular Value Decomposition for Image and Video Processing. ICCV Workshops (2017)
Seth D. Pendergrass, Steven L. Brunton, J. Nathan Kutz, N. Benjamin Erichson, Travis Askham
Dynamic Mode Decomposition for Background Modeling. ICCV Workshops (2017)
N. Benjamin Erichson, Ariana Mendible, Sophie Wihlborn, J. Nathan Kutz
Randomized Nonnegative Matrix Factorization. CoRR (2017)
N. Benjamin Erichson, Steven L. Brunton, J. Nathan Kutz
Randomized Dynamic Mode Decomposition. CoRR (2017)
N. Benjamin Erichson, Carl Donovan
Randomized low-rank Dynamic Mode Decomposition for motion detection. Comput. Vis. Image Underst. 146 (2016)
N. Benjamin Erichson, Sergey Voronin, Steven L. Brunton, J. Nathan Kutz
Randomized Matrix Decompositions using R. CoRR (2016)
N. Benjamin Erichson, Carl Donovan
Randomized Low-Rank Dynamic Mode Decomposition for Motion Detection. CoRR (2015)
J. Nathan Kutz, Xing Fu, Steven L. Brunton, N. Benjamin Erichson
Multi-resolution Dynamic Mode Decomposition for Foreground/Background Separation and Object Tracking. ICCV Workshops (2015)
N. Benjamin Erichson, Steven L. Brunton, J. Nathan Kutz
Compressed Dynamic Mode Decomposition for Real-Time Object Detection. CoRR (2015)