Network Reliability With Geographically Correlated Failures. - Sebastian Neumayer; Eytan H. Modiano (INFOCOM, 2010)

Network Reliability under Random Circular Cuts. - Sebastian Neumayer; Eytan H. Modiano (GLOBECOM, 2011)

Assessing the Vulnerability of the Fiber Infrastructure to Disasters. - Sebastian Neumayer; Gil Zussman; Reuven Cohen; Eytan H. Modiano (IEEE/ACM Trans. Netw., 2011)

Assessing the effect of geographically correlated failures on interconnected power-communication networks. - Sebastian Neumayer; Eytan H. Modiano (SmartGridComm, 2013)

On the robustness of network infrastructures to disasters and physical attacks. - Sebastian Neumayer (2013)

Geographic max-flow and min-cut under a circular disk failure model. - Sebastian Neumayer; Alon Efrat; Eytan H. Modiano (Comput. Networks, 2015)

Network reliability under geographically correlated line and disk failure models. - Sebastian Neumayer; Eytan H. Modiano (Comput. Networks, 2016)

On a Projected Weiszfeld Algorithm. - Sebastian Neumayer; Max Nimmer; Gabriele Steidl; Henrike Stephani (SSVM, 2017)

Capturing the security effects of network segmentation via a continuous-time markov chain model. - Neal Wagner; Cem Safak Sahin; Jaime Peña 001; James Riordan; Sebastian Neumayer (SpringSim (ANSS), 2017)

Morphing of Manifold-Valued Images Inspired by Discrete Geodesics in Image Spaces. - Sebastian Neumayer; Johannes Persch; Gabriele Steidl (SIAM J. Imaging Sci., 2018)

Minimal Lipschitz Extensions for Vector-Valued Functions on Finite Graphs. - Johannes Hertrich; Miroslav Bacák; Sebastian Neumayer; Gabriele Steidl (SSVM, 2019)

Parseval Proximal Neural Networks. - Marzieh Hasannasab; Johannes Hertrich; Sebastian Neumayer; Gerlind Plonka; Simon Setzer; Gabriele Steidl (CoRR, 2019)

Transfer Operators from Optimal Transport Plans for Coherent Set Detection. - Péter Koltai; Johannes von Lindheim; Sebastian Neumayer; Gabriele Steidl (CoRR, 2020)

Stabilizing Invertible Neural Networks Using Mixture Models. - Paul Hagemann; Sebastian Neumayer (CoRR, 2020)

Convolutional Proximal Neural Networks and Plug-and-Play Algorithms. - Johannes Hertrich; Sebastian Neumayer; Gabriele Steidl (CoRR, 2020)

Convergence of the Time Discrete Metamorphosis Model on Hadamard Manifolds. - Alexander Effland; Sebastian Neumayer; Martin Rumpf (SIAM J. Imaging Sci., 2020)

Curve Based Approximation of Measures on Manifolds by Discrepancy Minimization. - Martin Ehler; Manuel Gräf; Sebastian Neumayer; Gabriele Steidl (Found. Comput. Math., 2021)

A Neural-Network-Based Convex Regularizer for Image Reconstruction. - Alexis Goujon; Sebastian Neumayer; Pakshal Bohra; Stanislas Ducotterd; Michael Unser (CoRR, 2022)

An Image Registration Model in Electron Backscatter Diffraction. - Manuel Gräf; Sebastian Neumayer; Ralf Hielscher; Gabriele Steidl; Moritz Liesegang; Tilmann Beck (SIAM J. Imaging Sci., 2022)

A Neural-Network-Based Convex Regularizer for Inverse Problems. - Alexis Goujon; Sebastian Neumayer; Pakshal Bohra; Stanislas Ducotterd; Michael Unser (IEEE Trans. Computational Imaging, 2023)

Stability of Image-Reconstruction Algorithms. - Pol del Aguila Pla; Sebastian Neumayer; Michael Unser (IEEE Trans. Computational Imaging, 2023)

Unbalanced Multi-marginal Optimal Transport. - Florian Beier; Johannes von Lindheim; Sebastian Neumayer; Gabriele Steidl (J. Math. Imaging Vis., 2023)

Approximation of Lipschitz Functions Using Deep Spline Neural Networks. - Sebastian Neumayer; Alexis Goujon; Pakshal Bohra; Michael Unser (SIAM J. Math. Data Sci., 2023)

Learning a Convex Patch-Based Synthesis Model via Deep Equilibrium. - Stanislas Ducotterd; Sebastian Neumayer; Michael Unser (ICASSP, 2024)

Wasserstein Gradient Flows for Moreau Envelopes of f-Divergences in Reproducing Kernel Hilbert Spaces. - Sebastian Neumayer; Viktor Stein; Gabriele Steidl; Nicolaj Rux (CoRR, 2024)

Stability of Data-Dependent Ridge-Regularization for Inverse Problems. - Sebastian Neumayer; Fabian Altekrüger (CoRR, 2024)

Iteratively Refined Image Reconstruction with Learned Attentive Regularizers. - Mehrsa Pourya; Sebastian Neumayer; Michael Unser (CoRR, 2024)

Generative Feature Training of Thin 2-Layer Networks. - Johannes Hertrich; Sebastian Neumayer (CoRR, 2024)

Improving Lipschitz-Constrained Neural Networks by Learning Activation Functions. - Stanislas Ducotterd; Alexis Goujon; Pakshal Bohra; Dimitris Perdios; Sebastian Neumayer; Michael Unser (J. Mach. Learn. Res., 2024)

On the Effect of Initialization: The Scaling Path of 2-Layer Neural Networks. - Sebastian Neumayer; Lénaïc Chizat; Michael Unser (J. Mach. Learn. Res., 2024)

Template-Based Image Reconstruction Facing Different Topologies. - Sebastian Neumayer; Antonia Topalovic (J. Sci. Comput., 2024)

Learning Weakly Convex Regularizers for Convergent Image-Reconstruction Algorithms. - Alexis Goujon; Sebastian Neumayer; Michael Unser (SIAM J. Imaging Sci., 2024)

Learning of Patch-Based Smooth-Plus-Sparse Models for Image Reconstruction. - Stanislas Ducotterd; Sebastian Neumayer; Michael Unser (CPAL, 2025)

DEALing with Image Reconstruction: Deep Attentive Least Squares. - Mehrsa Pourya; Erich Kobler; Michael Unser; Sebastian Neumayer (CoRR, 2025)