A phase-field formulation for dynamic cohesive fracture von Geelen, Rudy J.M., Liu, Yingjie, Hu, Tianchen, Tupek, Michael R., Dolbow, John E.

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An optimization‐based phase‐field method for continuous‐discontinuous crack propagation von Geelen, Rudy J. M., Liu, Yingjie, Dolbow, John E., Rodríguez-Ferran, Antonio

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Learning physics-based reduced-order models from data using nonlinear manifolds von Geelen, Rudy, Balzano, Laura, Wright, Stephen, Willcox, Karen

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Scale-bridging with the extended/generalized finite element method for linear elastodynamics von Geelen, Rudy, Plews, Julia, Dolbow, John

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Localized non-intrusive reduced-order modelling in the operator inference framework von Geelen, Rudy, Willcox, Karen

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Operator inference for non-intrusive model reduction with quadratic manifolds von Geelen, Rudy, Wright, Stephen, Willcox, Karen

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Learning latent space dynamics with model-form uncertainties: A stochastic reduced-order modeling approach von Yong, Jin Yi, Geelen, Rudy, Guilleminot, Johann

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Operator inference for non-intrusive model reduction with quadratic manifolds von Geelen, Rudy, Wright, Stephen, Willcox, Karen

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An extended/generalized phase‐field finite element method for crack growth with global‐local enrichment von Geelen, Rudy, Plews, Julia, Tupek, Michael, Dolbow, John

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Symplectic model reduction of Hamiltonian systems using data-driven quadratic manifolds von Sharma, Harsh, Mu, Hongliang, Buchfink, Patrick, Geelen, Rudy, Glas, Silke, Kramer, Boris

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An extended/generalized phase-field finite element method for crack growth with global-local enrichment von Geelen, Rudy, Plews, Julia, Tupek, Michael, Dolbow, John

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A Data-driven Approach to X-Ray Spectral Fitting: Quasi-deconvolution von Rhea, Carter, Hlavacek-Larrondo, Julie, Kraft, Ralph, Bogdan, Akos, Geelen, Rudy

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Learning Latent Space Dynamics with Model-Form Uncertainties: A Stochastic Reduced-Order Modeling Approach von Yong, Jin Yi, Geelen, Rudy, Guilleminot, Johann

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Learning latent representations in high-dimensional state spaces using polynomial manifold constructions von Geelen, Rudy, Balzano, Laura, Willcox, Karen

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Operator inference for non-intrusive model reduction with quadratic manifolds von Geelen, Rudy, Wright, Stephen, Willcox, Karen

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Learning physics-based reduced-order models from data using nonlinear manifolds von Geelen, Rudy, Balzano, Laura, Wright, Stephen, Willcox, Karen

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Learning Latent Space Dynamics with Model-Form Uncertainties: A Stochastic Reduced-Order Modeling Approach von Jin, Yi Yong, Geelen, Rudy, Guilleminot, Johann

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Symplectic model reduction of Hamiltonian systems using data-driven quadratic manifolds von Sharma, Harsh, Mu, Hongliang, Buchfink, Patrick, Geelen, Rudy, Glas, Silke, Kramer, Boris

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Learning latent representations in high-dimensional state spaces using polynomial manifold constructions von Geelen, Rudy, Balzano, Laura, Willcox, Karen

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Learning physics-based reduced-order models from data using nonlinear manifolds von Geelen, Rudy, Balzano, Laura, Wright, Stephen, Willcox, Karen

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