Kutz, J. Nathan

Discovering governing equations from data by sparse identification of nonlinear dynamical systems

Brunton, S. L., Proctor, J. L., & Kutz, J. N. (2016) · Proceedings of the National Academy of Sciences

Model Reduction and Neural NetworksControl Systems and Identification

Cited by 4,796

Data-driven discovery of partial differential equations

Rudy, S. H., Brunton, S. L., Proctor, J. L., & Kutz, J. N. (2017) · Science Advances

Model Reduction and Neural NetworksControl Systems and Identification

Cited by 1,557

Data-driven discovery of coordinates and governing equations

Champion, K., Lusch, B., Kutz, J. N., & Brunton, S. L. (2019) · Proceedings of the National Academy of Sciences

Model Reduction and Neural NetworksControl Systems and Identification

Cited by 909

Inferring biological networks by sparse identification of nonlinear dynamics

Mangan, N. M., Brunton, S. L., Proctor, J. L., & Kutz, J. N. (2016) · IEEE Transactions on Molecular, Biological and Multi-Scale Communications

Gene Regulatory Network AnalysisControl Systems and Identification

Cited by 436

Data-driven modeling and learning in science and engineering

Montáns, F. J., Chinesta, F., Gómez-Bombarelli, R., & Kutz, J. N. (2019) · Comptes Rendus. Mécanique

Model Reduction and Neural NetworksMachine Learning in Materials Science

Cited by 299

Discovery of nonlinear multiscale systems: Sampling strategies and embeddings

Champion, K. P., Brunton, S. L., & Kutz, J. N. (2019) · SIAM Journal on Applied Dynamical Systems

Model Reduction and Neural NetworksControl Systems and Identification

Cited by 171

Predicting the functional effect of compound heterozygous genotypes from large scale variant effect maps

Xie, M. J., Cromie, G. A., Owens, K., Timour, M. S., Tang, M., Kutz, J. N., El-Hattab, A. W., McLaughlin, R. N., & Dudley, A. M. (2023) · PLoS Genetics

Genomics and Rare DiseasesMetabolism and Genetic Disorders

Cited by 6