Kutz, J. Nathan

11 publications

JMLR 2025 A Unified Framework to Enforce, Discover, and Promote Symmetry in Machine Learning Samuel E. Otto, Nicholas Zolman, J. Nathan Kutz, Steven L. Brunton

NeurIPS 2025 Common Task Framework for a Critical Evaluation of Scientific Machine Learning Algorithms Philippe Martin Wyder, Judah A Goldfeder, Alexey Yermakov, Yue Zhao, Stefano Riva, Jan P. Williams, David Zoro, Amy Sara Rude, Matteo Tomasetto, Joe Germany, Joseph Bakarji, Georg Maierhofer, Miles Cranmer, J. Nathan Kutz

L4DC 2025 Physics-Enforced Reservoir Computing for Forecasting Spatiotemporal Systems Dima Tretiak, Anastasia Bizyaeva, J. Nathan Kutz, Steven L. Brunton

MLOSS 2024 PyDMD: A Python Package for Robust Dynamic Mode Decomposition Sara M. Ichinaga, Francesco Andreuzzi, Nicola Demo, Marco Tezzele, Karl Lapo, Gianluigi Rozza, Steven L. Brunton, J. Nathan Kutz

NeurIPSW 2023 Attention for Causal Relationship Discovery from Biological Neural Dynamics Ziyu Lu, Anika Tabassum, Shruti R. Kulkarn, Lu Mi, J. Nathan Kutz, Eric Todd SheaBrown, Seung-Hwan Lim

JMLR 2023 Neural Implicit Flow: A Mesh-Agnostic Dimensionality Reduction Paradigm of Spatio-Temporal Data Shaowu Pan, Steven L. Brunton, J. Nathan Kutz

JMLR 2021 From Fourier to Koopman: Spectral Methods for Long-Term Time Series Prediction Henning Lange, Steven L. Brunton, J. Nathan Kutz

NeurIPSW 2019 Insect Cyborgs: Bio-Mimetic Feature Generators Improve ML Accuracy on Limited Data Charles B. Delahunt, J. Nathan Kutz

ICCVW 2017 Compressed Singular Value Decomposition for Image and Video Processing N. Benjamin Erichson, Steven L. Brunton, J. Nathan Kutz

ICCVW 2017 Dynamic Mode Decomposition for Background Modeling Seth D. Pendergrass, Steven L. Brunton, J. Nathan Kutz, N. Benjamin Erichson, Travis Askham

ICCVW 2015 Multi-Resolution Dynamic Mode Decomposition for Foreground/Background Separation and Object Tracking J. Nathan Kutz, Xing Fu, Steven L. Brunton, N. Benjamin Erichson