| Publication | Date of Publication | Type |
|---|
| Multiscale model reduction for incompressible flows | 2023-10-17 | Paper |
| Interpolatory input and output projections for flow control | 2023-09-27 | Paper |
| Parsimony as the ultimate regularizer for physics-informed machine learning | 2023-08-16 | Paper |
| Bounded nonlinear forecasts of partially observed geophysical systems with physics-constrained deep learning | 2023-03-09 | Paper |
| Distributed Control of Partial Differential Equations Using Convolutional Reinforcement Learning | 2023-01-25 | Paper |
| Multiresolution convolutional autoencoders | 2023-01-11 | Paper |
| Mobile Sensor Path Planning for Kalman Filter Spatiotemporal Estimation | 2022-12-15 | Paper |
| Optimal Sensor and Actuator Selection Using Balanced Model Reduction | 2022-07-28 | Paper |
| Modern Koopman Theory for Dynamical Systems | 2022-05-12 | Paper |
| Projection-tree reduced-order modeling for fast \(N\)-body computations | 2022-05-11 | Paper |
| Nonlinear System Level Synthesis for Polynomial Dynamical Systems | 2022-05-04 | Paper |
| Data-driven modeling of two-dimensional detonation wave fronts | 2022-04-14 | Paper |
| Data-Driven Science and Engineering | 2022-04-06 | Paper |
| On the role of nonlinear correlations in reduced-order modelling | 2022-03-11 | Paper |
| Data-driven stochastic modeling of coarse-grained dynamics with finite-size effects using Langevin regression | 2022-02-21 | Paper |
| Deep learning of conjugate mappings | 2022-02-21 | Paper |
| Near-wake dynamics of a vertical-axis turbine | 2022-01-27 | Paper |
| Data-Driven Sparse Sensor Placement for Reconstruction: Demonstrating the Benefits of Exploiting Known Patterns | 2022-01-10 | Paper |
| Deep learning models for global coordinate transformations that linearise PDEs | 2021-12-08 | Paper |
| Ensemble-SINDy: Robust sparse model discovery in the low-data, high-noise limit, with active learning and control | 2021-11-22 | Paper |
| Shallow neural networks for fluid flow reconstruction with limited sensors | 2021-10-29 | Paper |
| SINDy-PI: a robust algorithm for parallel implicit sparse identification of nonlinear dynamics | 2021-10-29 | Paper |
| Deeptime: a Python library for machine learning dynamical models from time series data | 2021-10-28 | Paper |
| Phase-based control of periodic flows | 2021-10-13 | Paper |
| Challenges in Dynamic Mode Decomposition | 2021-09-03 | Paper |
| SINDy with Control: A Tutorial | 2021-08-30 | Paper |
| https://portal.mardi4nfdi.de/entity/Q4998931 | 2021-07-09 | Paper |
| Data-driven Modeling of Two-Dimensional Detonation Wave Fronts | 2021-06-30 | Paper |
| 7 Data-driven methods for reduced-order modeling | 2021-06-15 | Paper |
| 9 From the POD-Galerkin method to sparse manifold models | 2021-06-15 | Paper |
| Data-driven resolvent analysis | 2021-05-20 | Paper |
| Deep learning of dynamics and signal-noise decomposition with time-stepping constraints | 2021-01-27 | Paper |
| Smoothing and parameter estimation by soft-adherence to governing equations | 2021-01-27 | Paper |
| Structured Time-Delay Models for Dynamical Systems with Connections to Frenet-Serret Frame | 2021-01-20 | Paper |
| DeepGreen: Deep Learning of Green's Functions for Nonlinear Boundary Value Problems | 2020-12-31 | Paper |
| Data-driven approximations of dynamical systems operators for control | 2020-11-19 | Paper |
| Machine Learning for Fluid Mechanics | 2020-07-07 | Paper |
| Sparse Principal Component Analysis via Variable Projection | 2020-05-21 | Paper |
| Time-Delay Observables for Koopman: Theory and Applications | 2020-05-11 | Paper |
| PySINDy: A Python package for the Sparse Identification of Nonlinear Dynamics from Data | 2020-04-17 | Paper |
| Multiresolution Convolutional Autoencoders | 2020-04-10 | Paper |
| Data-driven discovery of coordinates and governing equations | 2020-03-04 | Paper |
| Randomized Dynamic Mode Decomposition | 2020-01-03 | Paper |
| Model selection for hybrid dynamical systems via sparse regression | 2019-12-06 | Paper |
| Sparse identification of nonlinear dynamics for model predictive control in the low-data limit | 2019-11-19 | Paper |
| Randomized methods to characterize large-scale vortical flow network | 2019-09-02 | Paper |
| Cluster-based feedback control of turbulent post-stall separated flows | 2019-08-27 | Paper |
| Constrained sparse Galerkin regression | 2019-07-31 | Paper |
| Data-Driven Identification of Parametric Partial Differential Equations | 2019-06-20 | Paper |
| Discovery of Nonlinear Multiscale Systems: Sampling Strategies and Embeddings | 2019-06-14 | Paper |
| Optimized Sampling for Multiscale Dynamics | 2019-03-11 | Paper |
| Applied Koopman theory for partial differential equations and data-driven modeling of spatio-temporal systems | 2019-02-19 | Paper |
| Model selection for dynamical systems via sparse regression and information criteria | 2019-01-09 | Paper |
| Data-Driven Science and Engineering | 2019-01-08 | Paper |
| Optimal Sensor and Actuator Selection using Balanced Model Reduction | 2018-12-04 | Paper |
| Generalizing Koopman Theory to Allow for Inputs and Control | 2018-07-06 | Paper |
| Sparse reduced-order modelling: sensor-based dynamics to full-state estimation | 2018-06-05 | Paper |
| Greedy Sensor Placement with Cost Constraints | 2018-05-09 | Paper |
| Neural-inspired sensors enable sparse, efficient classification of spatiotemporal data | 2018-04-20 | Paper |
| Leveraging Sparsity and Compressive Sensing for Reduced Order Modeling | 2018-04-18 | Paper |
| Sparse Principal Component Analysis via Variable Projection | 2018-04-01 | Paper |
| Online Interpolation Point Refinement for Reduced-Order Models using a Genetic Algorithm | 2018-02-21 | Paper |
| Deep learning for universal linear embeddings of nonlinear dynamics | 2017-12-27 | Paper |
| Sparsity enabled cluster reduced-order models for control | 2017-12-01 | Paper |
| Sidelobe Canceling for Reconfigurable Holographic Metamaterial Antenna | 2017-10-30 | Paper |
| Data-driven discovery of Koopman eigenfunctions for control | 2017-07-04 | Paper |
| Frequency selection by feedback control in a turbulent shear flow | 2017-04-04 | Paper |
| Network structure of two-dimensional decaying isotropic turbulence | 2017-03-31 | Paper |
| Discovering governing equations from data by sparse identification of nonlinear dynamical systems | 2017-02-16 | Paper |
| https://portal.mardi4nfdi.de/entity/Q2957673 | 2017-01-27 | Paper |
| Streaming GPU Singular Value and Dynamic Mode Decompositions | 2016-12-23 | Paper |
| Long-time uncertainty propagation using generalized polynomial chaos and flow map composition | 2016-12-20 | Paper |
| Machine learning control -- taming nonlinear dynamics and turbulence | 2016-11-18 | Paper |
| Sparse Sensor Placement Optimization for Classification | 2016-10-28 | Paper |
| Compressed sensing and dynamic mode decomposition | 2016-09-30 | Paper |
| Chaos as an Intermittently Forced Linear System | 2016-08-18 | Paper |
| Inferring biological networks by sparse identification of nonlinear dynamics | 2016-05-26 | Paper |
| Sparse Identification of Nonlinear Dynamics with Control (SINDYc) | 2016-05-21 | Paper |
| Multiresolution Dynamic Mode Decomposition | 2016-05-20 | Paper |
| Discovering governing equations from data by sparse identification of nonlinear dynamical systems | 2016-03-28 | Paper |
| Dynamic Mode Decomposition with Control | 2016-03-08 | Paper |
| Koopman invariant subspaces and finite linear representations of nonlinear dynamical systems for control | 2015-10-10 | Paper |
| Fast computation of finite-time Lyapunov exponent fields for unsteady flows | 2015-05-19 | Paper |
| On dynamic mode decomposition: theory and applications | 2015-01-29 | Paper |
| Compressive Sensing and Low-Rank Libraries for Classification of Bifurcation Regimes in Nonlinear Dynamical Systems | 2015-01-20 | Paper |
| Reduced-order unsteady aerodynamic models at low Reynolds numbers | 2014-05-21 | Paper |
