Jan Robine

According to our database, Jan Robine authored at least 10 papers between 2020 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2025

A survey on self-supervised methods for visual representation learning.

Tobias Uelwer, Jan Robine, Stefan Sylvius Wagner, Marc Höftmann, Eric Upschulte, Sebastian Konietzny, Maike Behrendt, Stefan Harmeling

Mach. Learn., April, 2025

Simple, Good, Fast: Self-Supervised World Models Free of Baggage.

Jan Robine, Marc Höftmann, Stefan Harmeling

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2023

Smaller World Models for Reinforcement Learning.

Jan Robine, Tobias Uelwer, Stefan Harmeling

Neural Process. Lett., December, 2023

Cyclophobic Reinforcement Learning.

Stefan Sylvius Wagner, Peter Arndt, Jan Robine, Stefan Harmeling

Trans. Mach. Learn. Res., 2023

Backward Learning for Goal-Conditioned Policies.

Marc Höftmann, Jan Robine, Stefan Harmeling

CoRR, 2023

Limited-Angle Tomography Reconstruction via Deep End-To-End Learning on Synthetic Data.

Thomas Germer, Jan Robine, Sebastian Konietzny, Stefan Harmeling, Tobias Uelwer

CoRR, 2023

A Survey on Self-Supervised Representation Learning.

Tobias Uelwer, Jan Robine, Stefan Sylvius Wagner, Marc Höftmann, Eric Upschulte, Sebastian Konietzny, Maike Behrendt, Stefan Harmeling

CoRR, 2023

Time-Myopic Go-Explore: Learning A State Representation for the Go-Explore Paradigm.

Marc Höftmann, Jan Robine, Stefan Harmeling

CoRR, 2023

Transformer-based World Models Are Happy With 100k Interactions.

Jan Robine, Marc Höftmann, Tobias Uelwer, Stefan Harmeling

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2020

Discrete Latent Space World Models for Reinforcement Learning.

Jan Robine, Tobias Uelwer, Stefan Harmeling

CoRR, 2020