| Deep learning to discover and predict dynamics on an inertial manifold AJ Linot, MD Graham Physical Review E 101 (6), 062209, 2020 | 95 | 2020 |
| Stabilized neural ordinary differential equations for long-time forecasting of dynamical systems AJ Linot, JW Burby, Q Tang, P Balaprakash, MD Graham, R Maulik Journal of Computational Physics 474, 111838, 2023 | 68 | 2023 |
| Data-driven reduced-order modeling of spatiotemporal chaos with neural ordinary differential equations AJ Linot, MD Graham Chaos: An Interdisciplinary Journal of Nonlinear Science 32 (7), 2022 | 52 | 2022 |
| Data-driven control of spatiotemporal chaos with reduced-order neural ODE-based models and reinforcement learning K Zeng, AJ Linot, MD Graham Proceedings of the Royal Society A 478 (2267), 20220297, 2022 | 32 | 2022 |
| Turbulence control in plane Couette flow using low-dimensional neural ODE-based models and deep reinforcement learning AJ Linot, K Zeng, MD Graham International Journal of Heat and Fluid Flow 101, 109139, 2023 | 29 | 2023 |
| Dynamics of a data-driven low-dimensional model of turbulent minimal Couette flow AJ Linot, MD Graham Journal of Fluid Mechanics 973, A42, 2023 | 21 | 2023 |
| EnZymClass: Substrate specificity prediction tool of plant acyl-ACP thioesterases based on ensemble learning D Banerjee, MA Jindra, AJ Linot, BF Pfleger, CD Maranas Current Research in Biotechnology 4, 1-9, 2022 | 12 | 2022 |
| Enhancing predictive capabilities in data-driven dynamical modeling with automatic differentiation: Koopman and neural ODE approaches C Ricardo Constante-Amores, AJ Linot, MD Graham Chaos: An Interdisciplinary Journal of Nonlinear Science 34 (4), 2024 | 9 | 2024 |
| PyChannel AJ Linot, K Zeng, MD Graham | 5 | 2023 |
| Learning turbulence control strategies with data-driven reduced-order models and deep reinforcement learning K Zeng, A Linot, MD Graham 12th International Symposium on Turbulence and Shear Flow Phenomena (TSFP12 …, 2022 | 5 | 2022 |
| On the laminar solutions and stability of accelerating and decelerating channel flows AJ Linot, PJ Schmid, K Taira Journal of Fluid Mechanics 999, A43, 2024 | 2 | 2024 |
| Dynamics of a data-driven low-dimensional model of turbulent minimal pipe flow CR Constante-Amores, AJ Linot, MD Graham arXiv preprint arXiv:2408.03135, 2024 | 2 | 2024 |
| Building symmetries into data-driven manifold dynamics models for complex flows CEP De Jesús, AJ Linot, MD Graham arXiv preprint arXiv:2312.10235, 2023 | 1 | 2023 |
| Building symmetries into data-driven manifold dynamics models for complex flows CE Pérez De Jesús, AJ Linot, MD Graham arXiv e-prints, arXiv: 2312.10235, 2023 | 1 | 2023 |
| Reinforcement Learning With Symmetry Reduction for Rotating Cylinder Wakes: Finding Unstable Low-Drag Fixed Points H Omichi, AJ Linot, K Fukagata, K Taira AIAA SCITECH 2025 Forum, 1299, 2025 | | 2025 |
| Hierarchical equivariant graph neural networks for forecasting collective motion in vortex clusters and microswimmers AJ Linot, H Hang, E Kanso, K Taira arXiv preprint arXiv:2501.00626, 2024 | | 2024 |
| Avoiding explosive transient growth in laminar planar flows with optimal deceleration profiles A Linot, K Taira APS Division of Fluid Dynamics Meeting Abstracts, A24. 008, 2024 | | 2024 |
| Distributed Low-Dimensional Models for Predicting Large Spatiotemporally Chaotic Dynamical Systems CR Constante Amores, A Linot, M Graham APS Division of Fluid Dynamics Meeting Abstracts, ZC12. 003, 2024 | | 2024 |
| Data-driven prediction of large-scale spatiotemporal chaos with distributed low-dimensional models CR Constante-Amores, AJ Linot, MD Graham arXiv preprint arXiv:2410.01238, 2024 | | 2024 |
| Data-driven symmetry-aware low-dimensional models for predicting turbulent fluid flows C Perez De Jesus, A Linot, M Graham Bulletin of the American Physical Society, 2023 | | 2023 |
Michael D. GrahamSteenbock Professor of Engineering, Dept. of Chemical and Biological Engineering, UW-MadisonEmail verificata su wisc.edu