Bingni W. Brunton
Bingni W. Brunton
Professor, Richard and Joan Komen University Chair, University of Washington, Seattle
Verified email at - Homepage
Cited by
Cited by
Dynamic Mode Decomposition: Data-Driven Modeling of Complex Systems
JN Kutz, SL Brunton, BW Brunton, JL Proctor
Society for Industrial and Applied Mathematics, 2016
Rats and Humans Can Optimally Accumulate Evidence for Decision-Making
BW Brunton, MM Botvinick, CD Brody
Science 340 (6128), 95-98, 2013
Koopman Invariant Subspaces and Finite Linear Representations of Nonlinear Dynamical Systems for Control
SL Brunton, BW Brunton, JL Proctor, JN Kutz
PLOS ONE 11 (2), e0150171, 2016
Chaos as an intermittently forced linear system
SL Brunton, BW Brunton, JL Proctor, E Kaiser, JN Kutz
Nature Communications 8, 2017
Distinct relationships of parietal and prefrontal cortices to evidence accumulation
TD Hanks, CD Kopec, BW Brunton, CA Duan, JC Erlich, CD Brody
Nature 520 (7546), 220-223, 2015
Extracting spatial–temporal coherent patterns in large-scale neural recordings using dynamic mode decomposition
BW Brunton, LA Johnson, JG Ojemann, JN Kutz
Journal of neuroscience methods 258, 1-15, 2016
Cell shape and cell-wall organization in Gram-negative bacteria
KC Huang, R Mukhopadhyay, B Wen, Z Gitai, NS Wingreen
Proceedings of the National Academy of Sciences 105 (49), 19282-19287, 2008
Data-Driven Sparse Sensor Placement for Reconstruction: Demonstrating the Benefits of Exploiting Known Patterns
K Manohar, BW Brunton, JN Kutz, SL Brunton
IEEE Control Systems 38 (3), 63-86, 2018
Distinct effects of prefrontal and parietal cortex inactivations on an accumulation of evidence task in the rat
JC Erlich, BW Brunton, CA Duan, TD Hanks, CD Brody
Elife 4, e05457, 2015
Anipose: a toolkit for robust markerless 3D pose estimation
P Karashchuk, KL Rupp, ES Dickinson, S Walling-Bell, E Sanders, E Azim, ...
Cell Reports 36 (13), 109730, 2021
Ensemble-SINDy: Robust sparse model discovery in the low-data, high-noise limit, with active learning and control
U Fasel, JN Kutz, BW Brunton, SL Brunton
Proceedings of the Royal Society A 478 (2260), 20210904, 2022
Sparse Sensor Placement Optimization for Classification
BW Brunton, SL Brunton, JL Proctor, JN Kutz
SIAM Journal on Applied Mathematics 76 (5), 2099-2122, 2016
Cortical and Subcortical Contributions to Short-Term Memory for Orienting Movements
CD Kopec, JC Erlich, BW Brunton, K Deisseroth, CD Brody
Neuron 88 (2), 367-377, 2015
Numerical differentiation of noisy data: A unifying multi-objective optimization framework
F van Breugel, JN Kutz, BW Brunton
IEEE Access 8, 196865 - 196877, 2020
Exploiting sparsity and equation-free architectures in complex systems
JL Proctor, SL Brunton, BW Brunton, JN Kutz
The European Physical Journal Special Topics 223 (13), 2665-2684, 2014
Learning dominant physical processes with data-driven balance models
JL Callaham, JV Koch, BW Brunton, JN Kutz, SL Brunton
Nature Communications 12 (1), 1-10, 2021
Sindy with control: A tutorial
U Fasel, E Kaiser, JN Kutz, BW Brunton, SL Brunton
2021 60th IEEE Conference on Decision and Control (CDC), 16-21, 2021
Neural-inspired sensors enable sparse, efficient classification of spatiotemporal data
TL Mohren, TL Daniel, SL Brunton, BW Brunton
Proceedings of the National Academy of Science 115 (42), 10564--10569, 2018
Centering data improves the dynamic mode decomposition
SM Hirsh, KD Harris, JN Kutz, BW Brunton
SIAM Journal on Applied Dynamical Systems 19 (3), 1920-1955, 2020
Data-driven methods in fluid dynamics: Sparse classification from experimental data
Z Bai, SL Brunton, BW Brunton, JN Kutz, E Kaiser, A Spohn, BR Noack
Whither Turbulence and Big Data in the 21st Century?, 323-342, 2017
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