N. Benjamin Erichson

CoRR, 2024

Elucidating the Design Choice of Probability Paths in Flow Matching for Forecasting.

[BibT_eX]

[DOI]

CoRR, 2024

Tuning Frequency Bias of State Space Models.

[BibT_eX]

[DOI]

CoRR, 2024

Learning Physics for Unveiling Hidden Earthquake Ground Motions via Conditional Generative Modeling.

[BibT_eX]

[DOI]

CoRR, 2024

WaveCastNet: An AI-enabled Wavefield Forecasting Framework for Earthquake Early Warning.

[BibT_eX]

[DOI]

CoRR, 2024

There is HOPE to Avoid HiPPOs for Long-memory State Space Models.

[BibT_eX]

[DOI]

Annan Yu

CoRR, 2024

Robustifying State-space Models for Long Sequences via Approximate Diagonalization.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Generative Modeling of Regular and Irregular Time Series Data via Koopman VAEs.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Learning Representations, 2024

NoisyMix: Boosting Model Robustness to Common Corruptions.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

SuperBench: A Super-Resolution Benchmark Dataset for Scientific Machine Learning.

[BibT_eX]

[DOI]

CoRR, 2023

Randomized Numerical Linear Algebra : A Perspective on the Field With an Eye to Software.

[BibT_eX]

[DOI]

CoRR, 2023

Error Estimation for Random Fourier Features.

[BibT_eX]

[DOI]

Junwen Yao

Miles E. Lopes

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Gated Recurrent Neural Networks with Weighted Time-Delay Feedback.

[BibT_eX]

[DOI]

Soon Hoe Lim

CoRR, 2022

Learning continuous models for continuous physics.

[BibT_eX]

[DOI]

Aditi S. Krishnapriyan

CoRR, 2022

NoisyMix: Boosting Robustness by Combining Data Augmentations, Stability Training, and Noise Injections.

[BibT_eX]

[DOI]

CoRR, 2022

Long Expressive Memory for Sequence Modeling.

[BibT_eX]

[DOI]

Proceedings of the Tenth International Conference on Learning Representations, 2022

Noisy Feature Mixup.

[BibT_eX]

[DOI]

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Cluster-and-Conquer: A Framework For Time-Series Forecasting.

[BibT_eX]

[DOI]

CoRR, 2021

Compressing Deep ODE-Nets using Basis Function Expansions.

[BibT_eX]

[DOI]

Liam Hodgkinson

CoRR, 2021

A Differential Geometry Perspective on Orthogonal Recurrent Models.

[BibT_eX]

[DOI]

CoRR, 2021

Noise-Response Analysis of Deep Neural Networks Quantifies Robustness and Fingerprints Structural Malware.

[BibT_eX]

[DOI]

Proceedings of the 2021 SIAM International Conference on Data Mining, 2021

Stateful ODE-Nets using Basis Function Expansions.

[BibT_eX]

[DOI]

Liam Hodgkinson

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

Noisy Recurrent Neural Networks.

[BibT_eX]

[DOI]

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

Adversarially-Trained Deep Nets Transfer Better: Illustration on Image Classification.

[BibT_eX]

[DOI]

Proceedings of the 9th International Conference on Learning Representations, 2021

Lipschitz Recurrent Neural Networks.

[BibT_eX]

[DOI]

Omri Azencot

Liam Hodgkinson

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

Sparse Principal Component Analysis via Variable Projection.

[BibT_eX]

[DOI]

SIAM J. Appl. Math., 2020

Randomized CP tensor decomposition.

[BibT_eX]

[DOI]

Mach. Learn. Sci. Technol., 2020

Continuous-in-Depth Neural Networks.

[BibT_eX]

[DOI]

Dane Taylor

CoRR, 2020

Noise-response Analysis for Rapid Detection of Backdoors in Deep Neural Networks.

[BibT_eX]

[DOI]

CoRR, 2020

Adversarially-Trained Deep Nets Transfer Better.

[BibT_eX]

[DOI]

CoRR, 2020

Lipschitz Recurrent Neural Networks.

[BibT_eX]

[DOI]

Omri Azencot

CoRR, 2020

JumpReLU: A Retrofit Defense Strategy for Adversarial Attacks.

[BibT_eX]

[DOI]

Zhewei Yao

Proceedings of the 9th International Conference on Pattern Recognition Applications and Methods, 2020

Error Estimation for Sketched SVD via the Bootstrap.

[BibT_eX]

[DOI]

Miles E. Lopes

Proceedings of the 37th International Conference on Machine Learning, 2020

Forecasting Sequential Data Using Consistent Koopman Autoencoders.

[BibT_eX]

[DOI]

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

RetinaMatch: Efficient Template Matching of Retina Images for Teleophthalmology.

[BibT_eX]

[DOI]

Brian T. Schowengerdt

Eric J. Seibel

IEEE Trans. Medical Imaging, 2019

Randomized Dynamic Mode Decomposition.

[BibT_eX]

[DOI]

SIAM J. Appl. Dyn. Syst., 2019

Compressed dynamic mode decomposition for background modeling.

[BibT_eX]

[DOI]

J. Real Time Image Process., 2019

Bootstrapping the Operator Norm in High Dimensions: Error Estimation for Covariance Matrices and Sketching.

[BibT_eX]

[DOI]

Miles E. Lopes

CoRR, 2019

Randomized methods to characterize large-scale vortical flow network.

[BibT_eX]

[DOI]

Zhe Bai

Muralikrishnan Gopalakrishnan Meena

Kunihiko Taira

CoRR, 2019

Physics-informed Autoencoders for Lyapunov-stable Fluid Flow Prediction.

[BibT_eX]

[DOI]

Michael Muehlebach

CoRR, 2019

Shallow Learning for Fluid Flow Reconstruction with Limited Sensors and Limited Data.

[BibT_eX]

[DOI]

CoRR, 2019

2018

Randomized nonnegative matrix factorization.

[BibT_eX]

[DOI]

Pattern Recognit. Lett., 2018

Sparse Principal Component Analysis via Variable Projection.

[BibT_eX]

[DOI]

CoRR, 2018

Diffusion Maps meet Nyström.

[BibT_eX]

[DOI]

CoRR, 2018

2017

Randomized Dynamic Mode Decomposition.

[BibT_eX]

[DOI]

CoRR, 2017

Dynamic Mode Decomposition for Background Modeling.

[BibT_eX]

[DOI]

Proceedings of the 2017 IEEE International Conference on Computer Vision Workshops, 2017

Compressed Singular Value Decomposition for Image and Video Processing.

[BibT_eX]

[DOI]

Proceedings of the 2017 IEEE International Conference on Computer Vision Workshops, 2017

2016

Randomized low-rank Dynamic Mode Decomposition for motion detection.

[BibT_eX]

[DOI]

Carl Donovan

Comput. Vis. Image Underst., 2016

Randomized Matrix Decompositions using R.

[BibT_eX]

[DOI]

CoRR, 2016

2015

Compressed Dynamic Mode Decomposition for Real-Time Object Detection.

[BibT_eX]

[DOI]