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Bingni W. Brunton
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2020 – today
- 2024
- [i15]Ricardo Vinuesa, Jean Rabault, Hossein Azizpour, Stefan Bauer, Bingni W. Brunton, Arne Elofsson, Elias Jarlebring, Hedvig Kjellström, Stefano Markidis, David Marlevi, Paola Cinnella, Steven L. Brunton:
Opportunities for machine learning in scientific discovery. CoRR abs/2405.04161 (2024) - 2023
- [j12]Satpreet H. Singh
, Floris van Breugel, Rajesh P. N. Rao, Bingni W. Brunton:
Emergent behaviour and neural dynamics in artificial agents tracking odour plumes. Nat. Mac. Intell. 5(1): 58-70 (2023) - [c6]Jennifer J. Sun, Lili Karashchuk, Amil Dravid, Serim Ryou, Sonia Fereidooni, John C. Tuthill, Aggelos K. Katsaggelos, Bingni W. Brunton, Georgia Gkioxari, Ann Kennedy, Yisong Yue, Pietro Perona:
BKinD-3D: Self-Supervised 3D Keypoint Discovery from Multi-View Videos. CVPR 2023: 9001-9010 - [i14]Mozes Jacobs, Bingni W. Brunton, Steven L. Brunton, J. Nathan Kutz, Ryan V. Raut:
HyperSINDy: Deep Generative Modeling of Nonlinear Stochastic Governing Equations. CoRR abs/2310.04832 (2023) - 2022
- [j11]Floris van Breugel, Yuying Liu
, Bingni W. Brunton, J. Nathan Kutz:
PyNumDiff: A Python package for numerical differentiation of noisy time-series data. J. Open Source Softw. 7(71): 4078 (2022) - [j10]Biraj Pandey
, Marius Pachitariu
, Bingni W. Brunton
, Kameron Decker Harris
:
Structured random receptive fields enable informative sensory encodings. PLoS Comput. Biol. 18(10): 1010484 (2022) - [i13]Burak Boyacioglu, Alice C. Schwarze, Bingni W. Brunton, Kristi A. Morgansen:
Neural-inspired Measurement Observability. CoRR abs/2206.02361 (2022) - [i12]Sabera Talukder, Jennifer J. Sun, Matthew Leonard, Bingni W. Brunton, Yisong Yue:
Deep Neural Imputation: A Framework for Recovering Incomplete Brain Recordings. CoRR abs/2206.08094 (2022) - [i11]Alice C. Schwarze, Sara M. Ichinaga, Bingni W. Brunton:
Network inference via process motifs for lagged correlation in linear stochastic processes. CoRR abs/2208.08871 (2022) - [i10]Jennifer J. Sun, Pierre Karashchuk, Amil Dravid, Serim Ryou, Sonia Fereidooni, John C. Tuthill, Aggelos K. Katsaggelos
, Bingni W. Brunton, Georgia Gkioxari, Ann Kennedy, Yisong Yue, Pietro Perona:
BKinD-3D: Self-Supervised 3D Keypoint Discovery from Multi-View Videos. CoRR abs/2212.07401 (2022) - 2021
- [j9]Brian M. de Silva
, Krithika Manohar
, Emily Clark, Bingni W. Brunton
, J. Nathan Kutz
, Steven L. Brunton
:
PySensors: A Python package for sparse sensor placement. J. Open Source Softw. 6(58): 2828 (2021) - [j8]Alison I. Weber
, Thomas L. Daniel, Bingni W. Brunton:
Wing structure and neural encoding jointly determine sensing strategies in insect flight. PLoS Comput. Biol. 17(8) (2021) - [j7]Kameron Decker Harris
, Aleksandr Y. Aravkin
, Rajesh Rao, Bingni Wen Brunton:
Time-Varying Autoregression with Low-Rank Tensors. SIAM J. Appl. Dyn. Syst. 20(4): 2335-2358 (2021) - [c5]Urban Fasel, Eurika Kaiser, J. Nathan Kutz, Bingni W. Brunton, Steven L. Brunton:
SINDy with Control: A Tutorial. CDC 2021: 16-21 - [c4]Emil Azadian, Gautham Velchuru, Nancy Wang, Steven M. Peterson, Valentina Staneva, Bingni W. Brunton:
Decoding Happiness from Neural and Video Recordings for Better Insight Into Emotional Processing in the Brain. EMBC 2021: 6747-6750 - [i9]Brian M. de Silva, Krithika Manohar, Emily Clark, Bingni W. Brunton, Steven L. Brunton, J. Nathan Kutz:
PySensors: A Python Package for Sparse Sensor Placement. CoRR abs/2102.13476 (2021) - [i8]Satpreet Harcharan Singh, Floris van Breugel, Rajesh P. N. Rao, Bingni Wen Brunton:
Emergent behavior and neural dynamics in artificial agents tracking turbulent plumes. CoRR abs/2109.12434 (2021) - [i7]Urban Fasel, J. Nathan Kutz, Bingni W. Brunton, Steven L. Brunton:
Ensemble-SINDy: Robust sparse model discovery in the low-data, high-noise limit, with active learning and control. CoRR abs/2111.10992 (2021) - 2020
- [j6]Floris van Breugel
, J. Nathan Kutz
, Bingni W. Brunton:
Numerical Differentiation of Noisy Data: A Unifying Multi-Objective Optimization Framework. IEEE Access 8: 196865-196877 (2020) - [j5]Seth M. Hirsh, Kameron Decker Harris
, J. Nathan Kutz, Bingni W. Brunton:
Centering Data Improves the Dynamic Mode Decomposition. SIAM J. Appl. Dyn. Syst. 19(3): 1920-1955 (2020) - [c3]Satpreet H. Singh
, Floris van Breugel, Rajesh P. N. Rao, Bingni W. Brunton:
Understanding biological plume tracking behavior using deep reinforcement-learning. ALIFE 2020: 750-752 - [i6]Satpreet H. Singh
, Steven M. Peterson, Rajesh P. N. Rao, Bingni W. Brunton:
Towards naturalistic human neuroscience and neuroengineering: behavior mining in long-term video and neural recordings. CoRR abs/2001.08349 (2020)
2010 – 2019
- 2019
- [j4]James M. Kunert-Graf, Kristian M. Eschenburg, David J. Galas, J. Nathan Kutz, Swati D. Rane, Bingni W. Brunton:
Extracting Reproducible Time-Resolved Resting State Networks Using Dynamic Mode Decomposition. Frontiers Comput. Neurosci. 13: 75 (2019) - [i5]Kameron Decker Harris, Aleksandr Y. Aravkin, Rajesh Rao, Bingni Wen Brunton:
Time-varying Autoregression with Low Rank Tensors. CoRR abs/1905.08389 (2019) - 2018
- [j3]Eurika Kaiser
, Marek Morzynski, Guillaume Daviller, J. Nathan Kutz, Bingni W. Brunton, Steven L. Brunton:
Sparsity enabled cluster reduced-order models for control. J. Comput. Phys. 352: 388-409 (2018) - [c2]Nancy Xin Ru Wang, Ali Farhadi, Rajesh P. N. Rao, Bingni W. Brunton:
AJILE Movement Prediction: Multimodal Deep Learning for Natural Human Neural Recordings and Video. AAAI 2018: 2524-2531 - 2017
- [i4]Krithika Manohar, Bingni W. Brunton, J. Nathan Kutz, Steven L. Brunton:
Data-Driven Sparse Sensor Placement. CoRR abs/1701.07569 (2017) - [i3]Nancy Xin Ru Wang, Ali Farhadi, Rajesh P. N. Rao, Bingni W. Brunton:
AJILE Movement Prediction: Multimodal Deep Learning for Natural Human Neural Recordings and Video. CoRR abs/1709.05939 (2017) - 2016
- [b1]J. Nathan Kutz, Steven L. Brunton, Bingni W. Brunton, Joshua L. Proctor:
Dynamic mode decomposition - data-driven modeling of complex systems. SIAM 2016, ISBN 978-1-611-97449-2, pp. 1-234 - [j2]Bingni W. Brunton, Steven L. Brunton, Joshua L. Proctor, J. Nathan Kutz:
Sparse Sensor Placement Optimization for Classification. SIAM J. Appl. Math. 76(5): 2099-2122 (2016) - [c1]Jing Wu, Benjamin R. Shuman, Bingni W. Brunton, Katherine M. Steele
, Jared D. Olson
, Rajesh P. N. Rao
, Jeffrey G. Ojemann:
Multistep model for predicting upper-limb 3D isometric force application from pre-movement electrocorticographic features. EMBC 2016: 1564-1567 - [i2]Jing Wu, Benjamin R. Shuman, Bingni W. Brunton, Katherine M. Steele, Jared D. Olson, Rajesh P. N. Rao, Jeffrey G. Ojemann:
Multistep Model for Predicting Upper-Limb 3D Isometric Force Application from Pre-Movement Electrocorticographic Features. CoRR abs/1605.05291 (2016) - 2013
- [j1]Jan Kubanek
, Lawrence H. Snyder, Bingni W. Brunton, Carlos D. Brody, Gerwin Schalk
:
A low-frequency oscillatory neural signal in humans encodes a developing decision variable. NeuroImage 83: 795-808 (2013) - [i1]Bingni W. Brunton, Steven L. Brunton, Joshua L. Proctor, J. Nathan Kutz:
Optimal Sensor Placement and Enhanced Sparsity for Classification. CoRR abs/1310.4217 (2013)
Coauthor Index
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last updated on 2024-06-10 21:25 CEST by the dblp team
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