Optimal Sensor Placement and Enhanced Sparsity for Classification. - Bingni W. Brunton; Steven L. Brunton; Joshua L. Proctor; J. Nathan Kutz (CoRR, 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)

Dynamic mode decomposition - data-driven modeling of complex systems. - J. Nathan Kutz; Steven L. Brunton; Bingni W. Brunton; Joshua L. Proctor (SIAM, 2016)

Multistep model for predicting upper-limb 3D isometric force application from pre-movement electrocorticographic features. - Jing Wu 015; Benjamin R. Shuman; Bingni W. Brunton; Katherine M. Steele; Jared D. Olson; Rajesh P. N. Rao; Jeffrey G. Ojemann (EMBC, 2016)

Sparse Sensor Placement Optimization for Classification. - Bingni W. Brunton; Steven L. Brunton; Joshua L. Proctor; J. Nathan Kutz (SIAM J. Appl. Math., 2016)

Data-Driven Sparse Sensor Placement. - Krithika Manohar; Bingni W. Brunton; J. Nathan Kutz; Steven L. Brunton (CoRR, 2017)

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 (AAAI, 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)

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)

Understanding biological plume tracking behavior using deep reinforcement-learning. - Satpreet H. Singh; Floris van Breugel; Rajesh P. N. Rao; Bingni W. Brunton (ALIFE, 2020)

Numerical Differentiation of Noisy Data: A Unifying Multi-Objective Optimization Framework. - Floris van Breugel; J. Nathan Kutz; Bingni W. Brunton (IEEE Access, 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)

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)

SINDy with Control: A Tutorial. - Urban Fasel; Eurika Kaiser; J. Nathan Kutz; Bingni W. Brunton; Steven L. Brunton (CDC, 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 (EMBC, 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)

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)

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)

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)

Time-Varying Autoregression with Low-Rank Tensors. - Kameron Decker Harris; Aleksandr Y. Aravkin; Rajesh Rao; Bingni Wen Brunton (SIAM J. Appl. Dyn. Syst., 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 (Zenodo, 2021)

Neural-inspired Measurement Observability. - Burak Boyacioglu; Alice C. Schwarze; Bingni W. Brunton; Kristi A. Morgansen (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)

Network inference via process motifs for lagged correlation in linear stochastic processes. - Alice C. Schwarze; Sara M. Ichinaga; Bingni W. Brunton (CoRR, 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)

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)

Structured random receptive fields enable informative sensory encodings. - Biraj Pandey; Marius Pachitariu; Bingni W. Brunton; Kameron Decker Harris (PLoS Comput. Biol., 2022)

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 (CVPR, 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)

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., 2023)

Opportunities for machine learning in scientific discovery. - 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 (CoRR, 2024)