Tobias Uelwer

According to our database, Tobias Uelwer authored at least 19 papers between 2019 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

Resource-Efficient Anonymization of Textual Data via Knowledge Distillation from Large Language Models.

Tobias Deußer, Max Hahnbück, Tobias Uelwer, Cong Zhao, Christian Bauckhage, Rafet Sifa

Proceedings of the 31st International Conference on Computational Linguistics, 2025

2023

Smaller World Models for Reinforcement Learning.

Jan Robine, Tobias Uelwer, Stefan Harmeling

Neural Process. Lett., December, 2023

Approaching phase retrieval with deep learning

Tobias Uelwer

PhD thesis, 2023

Learning Conditional Generative Models for Phase Retrieval.

Tobias Uelwer, Sebastian Konietzny, Alexander Oberstraß, Stefan Harmeling

J. Mach. Learn. Res., 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

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

2022

Optimizing Intermediate Representations of Generative Models for Phase Retrieval.

Tobias Uelwer, Sebastian Konietzny, Stefan Harmeling

Trans. Mach. Learn. Res., 2022

Deblurring Photographs of Characters Using Deep Neural Networks.

Thomas Germer, Tobias Uelwer, Stefan Harmeling

CoRR, 2022

2021

A Closer Look at Reference Learning for Fourier Phase Retrieval.

Tobias Uelwer, Nick Rucks, Stefan Harmeling

CoRR, 2021

Learning to Detect Adversarial Examples Based on Class Scores.

Tobias Uelwer, Felix Michels, Oliver De Candido

Proceedings of the KI 2021: Advances in Artificial Intelligence - 44th German Conference on AI, Virtual Event, September 27, 2021

Learning to Plan via a Multi-step Policy Regression Method.

Stefan Wagner, Michael Janschek, Tobias Uelwer, Stefan Harmeling

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2021, 2021

Non-iterative Phase Retrieval with Cascaded Neural Networks.

Tobias Uelwer, Tobias Hoffmann, Stefan Harmeling

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2021, 2021

2020

PyMatting: A Python Library for Alpha Matting.

Thomas Germer, Tobias Uelwer, Stefan Conrad, Stefan Harmeling

J. Open Source Softw., 2020

Discrete Latent Space World Models for Reinforcement Learning.

Jan Robine, Tobias Uelwer, Stefan Harmeling

CoRR, 2020

Phase Retrieval Using Conditional Generative Adversarial Networks.

Tobias Uelwer, Alexander Oberstraß, Stefan Harmeling

Proceedings of the 25th International Conference on Pattern Recognition, 2020

Fast Multi-Level Foreground Estimation.

Thomas Germer, Tobias Uelwer, Stefan Conrad, Stefan Harmeling

Proceedings of the 25th International Conference on Pattern Recognition, 2020

2019

On the Vulnerability of Capsule Networks to Adversarial Attacks.

Felix Michels, Tobias Uelwer, Eric Upschulte, Stefan Harmeling

CoRR, 2019