Learning Behavior-Grounded Event Segmentations. - Christian Gumbsch; Jan Kneissler; Martin V. Butz (CogSci, 2016)

A Computational Model for the Dynamical Learning of Event Taxonomies. - Christian Gumbsch; Sebastian Otte; Martin V. Butz (CogSci, 2017)

Hierarchical principles of embodied reinforcement learning: A review. - Manfred Eppe; Christian Gumbsch; Matthias Kerzel; Phuong D. H. Nguyen; Martin V. Butz; Stefan Wermter (CoRR, 2020)

I see where this is going: Modeling the development of infants' goal-predictive gaze. - Christian Gumbsch; Maurits Adam; Birgit Elsner; Martin V. Butz (CogSci, 2021)

Latent Event-Predictive Encodings through Counterfactual Regularization. - Dania Humaidan; Sebastian Otte; Christian Gumbsch; Charley M. Wu; Martin V. Butz (CogSci, 2021)

Sparsely Changing Latent States for Prediction and Planning in Partially Observable Domains. - Christian Gumbsch; Martin V. Butz; Georg Martius (NeurIPS, 2021)

Emergent Goal-Anticipatory Gaze in Infants via Event-Predictive Learning and Inference. - Christian Gumbsch; Maurits Adam; Birgit Elsner; Martin V. Butz (Cogn. Sci., 2021)

Autonomous Identification and Goal-Directed Invocation of Event-Predictive Behavioral Primitives. - Christian Gumbsch; Martin V. Butz; Georg Martius (IEEE Trans. Cogn. Dev. Syst., 2021)

Developing hierarchical anticipations via neural network-based event segmentation. - Christian Gumbsch; Maurits Adam; Birgit Elsner; Georg Martius; Martin V. Butz (ICDL, 2022)

Intelligent problem-solving as integrated hierarchical reinforcement learning. - Manfred Eppe; Christian Gumbsch; Matthias Kerzel; Phuong D. H. Nguyen; Martin V. Butz; Stefan Wermter (Nat. Mach. Intell., 2022)

Inference of affordances and active motor control in simulated agents. - Fedor Scholz; Christian Gumbsch; Sebastian Otte; Martin V. Butz (Frontiers Neurorobotics, 2022)

Learning Hierarchical World Models with Adaptive Temporal Abstractions from Discrete Latent Dynamics. - Christian Gumbsch; Noor Sajid; Georg Martius; Martin V. Butz (ICLR, 2024)

Learning Event-Based Temporal Abstractions for Hierarchical Prediction and Planning - Christian Gumbsch (2024)

SENSEI: Semantic Exploration Guided by Foundation Models to Learn Versatile World Models. - Cansu Sancaktar; Christian Gumbsch; Andrii Zadaianchuk; Pavel Kolev; Georg Martius (CoRR, 2025)

Reframing attention as a reinforcement learning problem for causal discovery. - Turan Orujlu; Christian Gumbsch; Martin V. Butz; Charley M. Wu (CoRR, 2025)