Pseudospectra of the Orr-Sommerfeld Operator. - Satish C. Reddy; Peter J. Schmid; Dan S. Henningson (SIAM J. Appl. Math., 1993)

A preconditioned Krylov technique for global hydrodynamic stability analysis of large-scale compressible flows. - Christoph J. Mack; Peter J. Schmid (J. Comput. Phys., 2010)

Iterative optimization based on an objective functional in frequency-space with application to jet-noise cancellation. - Jan Schulze; Peter J. Schmid; Jörn Sesterhenn (J. Comput. Phys., 2011)

Adjoint algorithms for the Navier-Stokes equations in the low Mach number limit. - Gary J. Chandler; Matthew P. Juniper; Joseph W. Nichols; Peter J. Schmid (J. Comput. Phys., 2012)

A relaxation method for large eigenvalue problems, with an application to flow stability analysis. - Xavier Garnaud; Lutz Lesshafft; Peter J. Schmid; J.-M. Chomaz (J. Comput. Phys., 2012)

Efficient evaluation of the direct and adjoint linearized dynamics from compressible flow solvers. - Miguel Fosas de Pando; Denis Sipp; Peter J. Schmid (J. Comput. Phys., 2012)

Hybrid Reduced-Order Integration with Proper Orthogonal Decomposition and Dynamic Mode Decomposition. - Matthew O. Williams; Peter J. Schmid; J. Nathan Kutz (Multiscale Model. Simul., 2013)

Erratum: Hybrid Reduced-Order Integration with Proper Orthogonal Decomposition and Dynamic Mode Decomposition. - Matthew O. Williams; Peter J. Schmid; J. Nathan Kutz (Multiscale Model. Simul., 2013)

Nonlinear model-order reduction for compressible flow solvers using the Discrete Empirical Interpolation Method. - Miguel Fosas de Pando; Peter J. Schmid; Denis Sipp (J. Comput. Phys., 2016)

A gradient-based framework for maximizing mixing in binary fluids. - Maximilian F. Eggl; Peter J. Schmid (J. Comput. Phys., 2018)

Nonlinear model reduction: a comparison between POD-Galerkin and POD-DEIM methods. - Denis Sipp; Miguel Fosas de Pando; Peter J. Schmid (CoRR, 2020)

Symmetry-Aware Autoencoders: s-PCA and s-nlPCA. - Simon Kneer; Taraneh Sayadi; Denis Sipp; Peter J. Schmid; Georgios Rigas (CoRR, 2021)

A parallel-in-time approach for accelerating direct-adjoint studies. - Calum S. Skene; Maximilian F. Eggl; Peter J. Schmid (J. Comput. Phys., 2021)

Data-driven framework for input/output lookup tables reduction - with application to hypersonic flows in chemical non-equilibrium. - Clément Scherding; Georgios Rigas; Denis Sipp; Peter J. Schmid; Taraneh Sayadi (CoRR, 2022)

Parallel-in-time adjoint-based optimization - application to unsteady incompressible flows. - S. Costanzo; Taraneh Sayadi; Miguel Fosas de Pando; Peter J. Schmid; P. Frey (J. Comput. Phys., 2022)

Mori-Zwanzig latent space Koopman closure for nonlinear autoencoder. - Priyam Gupta; Peter J. Schmid; Denis Sipp; Taraneh Sayadi; Georgios Rigas (CoRR, 2023)

RONAALP: Reduced-Order Nonlinear Approximation with Active Learning Procedure. - Clément Scherding; Georgios Rigas; Denis Sipp; Peter J. Schmid; Taraneh Sayadi (CoRR, 2023)

A robust computational framework for variational data assimilation of mean flows with sparse measurements corrupted by strong outliers. - Souvik Ghosh; Vincent Mons; Denis Sipp; Peter J. Schmid (J. Comput. Phys., 2024)

Sliding plane formalism for aeroacoustic and adjoint-based sensitivity calculations. - Anton Glazkov; Miguel Fosas de Pando; Peter J. Schmid; Li He (Comput. Phys. Commun., 2025)

An adaptive learning strategy for surrogate modeling of high-dimensional functions - Application to unsteady hypersonic flows in chemical nonequilibrium. - Clément Scherding; Georgios Rigas; Denis Sipp; Peter J. Schmid; Taraneh Sayadi (Comput. Phys. Commun., 2025)