Large-Scale Stochastic Scene Generation and Semantic Annotation for Deep Convolutional Neural Network Training in the RoboCup SPL. - Timm Hess; Martin Mundt; Tobias Weis; Visvanathan Ramesh (RoboCup, 2017)

A Procedural World Generation Framework for Systematic Evaluation of Continual Learning. - Timm Hess; Martin Mundt; Iuliia Pliushch; Visvanathan Ramesh (NeurIPS Datasets and Benchmarks, 2021)

Two Complementary Perspectives to Continual Learning: Ask Not Only What to Optimize, But Also How. - Timm Hess; Tinne Tuytelaars; Gido M. van de Ven (CoRR, 2023)

Knowledge Accumulation in Continually Learned Representations and the Issue of Feature Forgetting. - Timm Hess; Eli Verwimp; Gido M. van de Ven; Tinne Tuytelaars (Trans. Mach. Learn. Res., 2024)

Forgetting of task-specific knowledge in model merging-based continual learning. - Timm Hess; Gido M. van de Ven; Tinne Tuytelaars (CoRR, 2025)