Showing 21–40 of 195 results
/ Date/ Name
Apr 21, 2004Newton-Krylov solvers for time-steppersNov 16, 2001Coarse Bifurcation Studies of Bubble Flow Microscopic SimulationsNov 23, 2001Going with the Flow: a Lagrangian approach to self-similar dynamics and its consequencesDec 1, 2004An Equation-Free Approach to Nonlinear Control: Coarse Feedback Linearization With Pole-PlacementSep 9, 2005Coarse-graining the dynamics of coupled oscillatorsFeb 3, 2003Coarse Bifurcation Diagrams via Microscopic Simulators: A State-Feedback Control-Based ApproachJul 8, 2022Black and Gray Box Learning of Amplitude Equations: Application to Phase Field SystemsDec 21, 2023AI-Lorenz: A physics-data-driven framework for black-box and gray-box identification of chaotic systems with symbolic regressionNov 23, 2010Manifold learning techniques and model reduction applied to dissipative PDEsOct 28, 2022Two novel families of multiscale staggered patch schemes efficiently simulate large-scale, weakly damped, linear wavesMay 5, 2023Data-driven and Physics Informed Modelling of Chinese Hamster Ovary Cell BioreactorsOct 24, 2023Nonlinear dimensionality reduction then and now: AIMs for dissipative PDEs in the ML eraApr 5, 2011Noisy dynamic simulations in the presence of symmetry: data alignment and model reductionDec 4, 2018Some manifold learning considerations towards explicit model predictive controlJul 10, 2020Transformations between deep neural networksSep 12, 2019Coarse-scale PDEs from fine-scale observations via machine learningAug 18, 2020Exploring Critical Points of Energy Landscapes: From Low-Dimensional Examples to Phase Field Crystal PDEsJun 10, 2021Learning effective stochastic differential equations from microscopic simulations: linking stochastic numerics to deep learningMay 4, 2021Personalized Algorithm Generation: A Case Study in Learning ODE IntegratorsApr 15, 2020LOCA: LOcal Conformal Autoencoder for standardized data coordinates