Convex Joint Graph Matching and Clustering via Semidefinite Relaxations. - Maximilian Krahn; Florian Bernard; Vladislav Golyanik (3DV, 2021)

Shifting Our Awareness, Taking Back Tags: Temporal Changes in Computer Vision Services' Social Behaviors. - Pinar Barlas; Maximilian Krahn; Styliani Kleanthous; Kyriakos Kyriakou; Jahna Otterbacher (ICWSM, 2022)

QuAnt: Quantum Annealing with Learnt Couplings. - Marcel Seelbach Benkner; Maximilian Krahn; Edith Tretschk; Zorah Lähner; Michael Moeller 001; Vladislav Golyanik (ICLR, 2023)

TIDE: Time Derivative Diffusion for Deep Learning on Graphs. - Maysam Behmanesh; Maximilian Krahn; Maks Ovsjanikov (ICML, 2023)

Projected Stochastic Gradient Descent with Quantum Annealed Binary Gradients. - Maximilian Krahn; Michele Sasdelli; Frances Fengyi Yang; Vladislav Golyanik; Juho Kannala; Tat-Jun Chin; Tolga Birdal (BMVC, 2024)

Scheduling conditional task graphs with deep reinforcement learning. - Anton Debner; Maximilian Krahn; Vesa Hirvisalo (NLDL, 2024)

Heat Kernel Goes Topological. - Maximilian Krahn; Vikas Garg 001 (CoRR, 2025)