Bingni W. Brunton

According to our database, Bingni W. Brunton authored at least 29 papers between 2013 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2023

Emergent behaviour and neural dynamics in artificial agents tracking odour plumes.

Satpreet H. Singh, Floris van Breugel, Rajesh P. N. Rao, Bingni W. Brunton

Nat. Mac. Intell., January, 2023

HyperSINDy: Deep Generative Modeling of Nonlinear Stochastic Governing Equations.

Mozes Jacobs, Bingni W. Brunton, Steven L. Brunton, J. Nathan Kutz, Ryan V. Raut

CoRR, 2023

BKinD-3D: Self-Supervised 3D Keypoint Discovery from Multi-View Videos.

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

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

Structured random receptive fields enable informative sensory encodings.

Biraj Pandey, Marius Pachitariu, Bingni W. Brunton, Kameron Decker Harris

PLoS Comput. Biol., October, 2022

PyNumDiff: A Python package for numerical differentiation of noisy time-series data.

Floris van Breugel, Yuying Liu, Bingni W. Brunton, J. Nathan Kutz

J. Open Source Softw., 2022

BKinD-3D: Self-Supervised 3D Keypoint Discovery from Multi-View Videos.

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

CoRR, 2022

Network inference via process motifs for lagged correlation in linear stochastic processes.

Alice C. Schwarze, Sara M. Ichinaga, Bingni W. Brunton

CoRR, 2022

Deep Neural Imputation: A Framework for Recovering Incomplete Brain Recordings.

Sabera Talukder, Jennifer J. Sun, Matthew Leonard, Bingni W. Brunton, Yisong Yue

CoRR, 2022

Neural-inspired Measurement Observability.

Burak Boyacioglu, Alice C. Schwarze, Bingni W. Brunton, Kristi A. Morgansen

CoRR, 2022

2021

Time-Varying Autoregression with Low-Rank Tensors.

Kameron Decker Harris, Aleksandr Y. Aravkin, Rajesh Rao, Bingni Wen Brunton

SIAM J. Appl. Dyn. Syst., 2021

Wing structure and neural encoding jointly determine sensing strategies in insect flight.

Alison I. Weber, Thomas L. Daniel, Bingni W. Brunton

PLoS Comput. Biol., 2021

PySensors: A Python package for sparse sensor placement.

Brian M. de Silva, Krithika Manohar, Emily Clark, Bingni W. Brunton, J. Nathan Kutz, Steven L. Brunton

J. Open Source Softw., 2021

Ensemble-SINDy: Robust sparse model discovery in the low-data, high-noise limit, with active learning and control.

Urban Fasel, J. Nathan Kutz, Bingni W. Brunton, Steven L. Brunton

CoRR, 2021

Emergent behavior and neural dynamics in artificial agents tracking turbulent plumes.

Satpreet Harcharan Singh, Floris van Breugel, Rajesh P. N. Rao, Bingni Wen Brunton

CoRR, 2021

Decoding Happiness from Neural and Video Recordings for Better Insight Into Emotional Processing in the Brain.

Emil Azadian, Gautham Velchuru, Nancy Wang, Steven M. Peterson, Valentina Staneva, Bingni W. Brunton

Proceedings of the 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2021

SINDy with Control: A Tutorial.

Urban Fasel, Eurika Kaiser, J. Nathan Kutz, Bingni W. Brunton, Steven L. Brunton

Proceedings of the 2021 60th IEEE Conference on Decision and Control (CDC), 2021

2020

Centering Data Improves the Dynamic Mode Decomposition.

Seth M. Hirsh, Kameron Decker Harris, J. Nathan Kutz, Bingni W. Brunton

SIAM J. Appl. Dyn. Syst., 2020

Towards naturalistic human neuroscience and neuroengineering: behavior mining in long-term video and neural recordings.

Satpreet H. Singh, Steven M. Peterson, Rajesh P. N. Rao, Bingni W. Brunton

CoRR, 2020

Numerical Differentiation of Noisy Data: A Unifying Multi-Objective Optimization Framework.

Floris van Breugel, J. Nathan Kutz, Bingni W. Brunton

IEEE Access, 2020

Understanding biological plume tracking behavior using deep reinforcement-learning.

Satpreet H. Singh, Floris van Breugel, Rajesh P. N. Rao, Bingni W. Brunton

Proceedings of the 2020 Conference on Artificial Life, 2020

2019

Extracting Reproducible Time-Resolved Resting State Networks Using Dynamic Mode Decomposition.

James M. Kunert-Graf, Kristian M. Eschenburg, David J. Galas, J. Nathan Kutz, Swati D. Rane, Bingni W. Brunton

Frontiers Comput. Neurosci., 2019

2018

Sparsity enabled cluster reduced-order models for control.

Eurika Kaiser, Marek Morzynski, Guillaume Daviller, J. Nathan Kutz, Bingni W. Brunton, Steven L. Brunton

J. Comput. Phys., 2018

AJILE Movement Prediction: Multimodal Deep Learning for Natural Human Neural Recordings and Video.

Nancy Xin Ru Wang, Ali Farhadi, Rajesh P. N. Rao, Bingni W. Brunton

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017

Data-Driven Sparse Sensor Placement.

Krithika Manohar, Bingni W. Brunton, J. Nathan Kutz, Steven L. Brunton

CoRR, 2017

2016

Sparse Sensor Placement Optimization for Classification.

Bingni W. Brunton, Steven L. Brunton, Joshua L. Proctor, J. Nathan Kutz

SIAM J. Appl. Math., 2016

Multistep model for predicting upper-limb 3D isometric force application from pre-movement electrocorticographic features.

Jing Wu, Benjamin R. Shuman, Bingni W. Brunton, Katherine M. Steele, Jared D. Olson, Rajesh P. N. Rao, Jeffrey G. Ojemann

Proceedings of the 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2016

Dynamic mode decomposition - data-driven modeling of complex systems.

J. Nathan Kutz, Steven L. Brunton, Bingni W. Brunton, Joshua L. Proctor

SIAM, ISBN: 978-1-611-97449-2, 2016

2013

A low-frequency oscillatory neural signal in humans encodes a developing decision variable.

Jan Kubanek, Lawrence H. Snyder, Bingni W. Brunton, Carlos D. Brody, Gerwin Schalk

NeuroImage, 2013

Optimal Sensor Placement and Enhanced Sparsity for Classification.

Bingni W. Brunton, Steven L. Brunton, Joshua L. Proctor, J. Nathan Kutz

CoRR, 2013