no code implementations • 7 May 2024 • Ricardo Vinuesa, Jean Rabault, Hossein Azizpour, Stefan Bauer, Bingni W. Brunton, Arne Elofsson, Elias Jarlebring, Hedvig Kjellstrom, Stefano Markidis, David Marlevi, Paola Cinnella, Steven L. Brunton
Technological advancements have substantially increased computational power and data availability, enabling the application of powerful machine-learning (ML) techniques across various fields.
no code implementations • 7 Oct 2023 • Mozes Jacobs, Bingni W. Brunton, Steven L. Brunton, J. Nathan Kutz, Ryan V. Raut
Taken together, HyperSINDy offers a promising framework for model discovery and uncertainty quantification in real-world systems, integrating sparse equation discovery methods with advances in statistical machine learning and deep generative modeling.
1 code implementation • CVPR 2023 • Jennifer J. Sun, Lili Karashchuk, Amil Dravid, Serim Ryou, Sonia Fereidooni, John Tuthill, Aggelos Katsaggelos, Bingni W. Brunton, Georgia Gkioxari, Ann Kennedy, Yisong Yue, Pietro Perona
In this way, we discover keypoints without requiring manual supervision in videos of humans and rats, demonstrating the potential of 3D keypoint discovery for studying behavior.
no code implementations • 18 Aug 2022 • Alice C. Schwarze, Sara M. Ichinaga, Bingni W. Brunton
Motivated by process motifs for lagged covariance in an autoregressive model with slow mean-reversion, we propose to infer networks of causal relations via pairwise edge measure (PEMs) that one can easily compute from lagged correlation matrices.
no code implementations • 16 Jun 2022 • Sabera Talukder, Jennifer J. Sun, Matthew Leonard, Bingni W. Brunton, Yisong Yue
Neuroscientists and neuroengineers have long relied on multielectrode neural recordings to study the brain.
no code implementations • 6 Jun 2022 • Burak Boyacıoğlu, Alice C. Schwarze, Bingni W. Brunton, Kristi A. Morgansen
The neural encoding by biological sensors of flying insects, which prefilters stimulus data before sending it to the central nervous system in the form of voltage spikes, enables sensing capabilities that are computationally low-cost while also being highly robust to noise.
4 code implementations • 20 Feb 2021 • Brian M. de Silva, Krithika Manohar, Emily Clark, Bingni W. Brunton, Steven L. Brunton, J. Nathan Kutz
PySensors is a Python package for selecting and placing a sparse set of sensors for classification and reconstruction tasks.
1 code implementation • 3 Sep 2020 • Floris van Breugel, J. Nathan Kutz, Bingni W. Brunton
Computing derivatives of noisy measurement data is ubiquitous in the physical, engineering, and biological sciences, and it is often a critical step in developing dynamic models or designing control.
Dynamical Systems Signal Processing
1 code implementation • 23 Jun 2020 • George Stepaniants, Bingni W. Brunton, J. Nathan Kutz
Our proposed PCI method demonstrated consistently strong performance in inferring causal relations for small (2-5 node) and large (10-20 node) networks, with both linear and nonlinear dynamics.
Dynamical Systems Adaptation and Self-Organizing Systems Applications 37M10, 62D20, 62M10
1 code implementation • 23 Jan 2020 • Satpreet H. Singh, Steven M. Peterson, Rajesh P. N. Rao, Bingni W. Brunton
We show results from our approach applied to data collected for 12 human subjects over 7--9 days for each subject.