Bing Wen Brunton
Bing Wen Brunton
Associate Professor, University of Washington
Vahvistettu sähköpostiosoite verkkotunnuksessa - Kotisivu
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
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
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
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
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 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
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
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
Sparse Sensor Placement Optimization for Classification
BW Brunton, SL Brunton, JL Proctor, JN Kutz
SIAM Journal on Applied Mathematics 76 (5), 2099-2122, 2016
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
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
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
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
AJILE Movement Prediction: Multimodal Deep Learning for Natural Human Neural Recordings and Video
XRN Wang, A Farhadi, R Rao, B Brunton
AAAI Conference on Artificial Intelligence, 2524, 2018
A low-frequency oscillatory neural signal in humans encodes a developing decision variable
J Kubanek, LH Snyder, BW Brunton, CD Brody, G Schalk
NeuroImage 83, 795-808, 2013
Unsupervised decoding of long-term, naturalistic human neural recordings with automated video and audio annotations
NXR Wang, JD Olson, JG Ojemann, RPN Rao, BW Brunton
Frontiers in Human Neuroscience 10, 165, 2016
Sparsity enabled cluster reduced-order models for control
E Kaiser, M Morzyński, G Daviller, JN Kutz, BW Brunton, SL Brunton
Journal of Computational Physics, 2017
Extracting reproducible time-resolved resting state networks using dynamic mode decomposition
JM Kunert-Graf, K Eschenburg, D Galas, JN Kutz, S Rane, BW Brunton
Frontiers in Computational Neuroscience 13, 75, 2019
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Artikkelit 1–20