Content Adaptive Optimization for Neural Image Compression. - Joaquim Campos; Simon Meierhans; Abdelaziz Djelouah; Christopher Schroers (CVPR Workshops, 2019)

Resilient Dictionaries for Randomly Unreliable Memory. - Stefano Leucci 001; Chih-Hung Liu 001; Simon Meierhans (ESA, 2019)

Transformations of High-Level Synthesis Codes for High-Performance Computing. - Johannes de Fine Licht; Maciej Besta; Simon Meierhans; Torsten Hoefler (IEEE Trans. Parallel Distributed Syst., 2021)

Derandomizing Directed Random Walks in Almost-Linear Time. - Rasmus Kyng; Simon Meierhans; Maximilian Probst (FOCS, 2022)

Incremental SSSP for Sparse Digraphs Beyond the Hopset Barrier. - Rasmus Kyng; Simon Meierhans; Maximilian Probst Gutenberg (SODA, 2022)

Almost-Linear Time Algorithms for Decremental Graphs: Min-Cost Flow and More via Duality. - Jan van den Brand; Li Chen 028; Rasmus Kyng; Yang P. Liu; Simon Meierhans; Maximilian Probst Gutenberg; Sushant Sachdeva (FOCS, 2024)

Almost-Linear Time Algorithms for Incremental Graphs: Cycle Detection, SCCs, s-t Shortest Path, and Minimum-Cost Flow. - Li Chen 028; Rasmus Kyng; Yang P. Liu; Simon Meierhans; Maximilian Probst Gutenberg (STOC, 2024)

A Dynamic Shortest Paths Toolbox: Low-Congestion Vertex Sparsifiers and Their Applications. - Rasmus Kyng; Simon Meierhans; Maximilian Probst Gutenberg (STOC, 2024)

Bootstrapping Dynamic APSP via Sparsification. - Rasmus Kyng; Simon Meierhans; Gernot Zöcklein (CoRR, 2024)

A Simple Dynamic Spanner via APSP. - Rasmus Kyng; Simon Meierhans; Gernot Zöcklein (ICALP, 2025)

Parallel and Distributed Expander Decomposition: Simple, Fast, and Near-Optimal. - Daoyuan Chen; Simon Meierhans; Maximilian Probst Gutenberg; Thatchaphol Saranurak (SODA, 2025)

Expander Pruning with Polylogarithmic Worst-Case Recourse and Update Time. - Simon Meierhans; Maximilian Probst Gutenberg; Thatchaphol Saranurak (CoRR, 2025)