Structure Learning for Bayesian Networks Using the Physarum Solver. - Torsten Schön; Martin Stetter; Elmar Wolfgang Lang (ICMLA (1), 2012)

Gene-pair representation and incorporation of GO-based semantic similarity into classification of gene expression data. - Torsten Schön; Alexey Tsymbal; Martin Huber 001 (Intell. Data Anal., 2012)

A New Physarum Learner for Network Structure Learning from Biomedical Data. - Torsten Schön; Martin Stetter; Ana Maria Tomé; Elmar Wolfgang Lang (BIOSIGNALS, 2013)

Physarum Learner: a novel structure learning algorithm for Bayesian Networks inspired by Physarum polycephalum. - Torsten Schön (2013)

Physarum Learner: A bio-inspired way of learning structure from data. - Torsten Schön; Martin Stetter; Ana Maria Tomé; Carlos García Puntonet; Elmar Wolfgang Lang (Expert Syst. Appl., 2014)

Latent Space Reinforcement Learning for Steering Angle Prediction. - Qadeer Khan; Torsten Schön; Patrick Wenzel (CoRR, 2019)

Semantic Label Reduction Techniques for Autonomous Driving. - Qadeer Khan; Torsten Schön; Patrick Wenzel (CoRR, 2019)

Towards Self-Supervised High Level Sensor Fusion. - Qadeer Khan; Torsten Schön; Patrick Wenzel (CoRR, 2019)

Vision-Based Mobile Robotics Obstacle Avoidance With Deep Reinforcement Learning. - Patrick Wenzel; Torsten Schön; Laura Leal-Taixé; Daniel Cremers (ICRA, 2021)

Temporally coherent video anonymization through GAN inpainting. - Thangapavithraa Balaji; Patrick Blies; Georg Göri; Raphael Mitsch; Marcel Wasserer; Torsten Schön (CoRR, 2021)

VolNet: Estimating Human Body Part Volumes from a Single RGB Image. - Fabian Leinen; Vittorio Cozzolino; Torsten Schön (CoRR, 2021)

Perceiver Hopfield Pooling for Dynamic Multi-modal and Multi-instance Fusion. - Dominik Rößle; Daniel Cremers; Torsten Schön (ICANN (1), 2022)

Enhancing Realistic Floating Car Observers in Microscopic Traffic Simulation. - Jeremias Gerner; Dominik Rößle; Daniel Cremers; Klaus Bogenberger; Torsten Schön; Stefanie Schmidtner (ITSC, 2023)

A novel Conditional Generative Adversarial Networks for Automotive Radar Range-Doppler Targets Synthetic Generation. - Diogo Wachtel; Samuel Queiroz; Torsten Schön; Werner Huber; Lester de Abreu Faria (ITSC, 2023)

Predicting Driver Behavior on the Highway with Multi-Agent Adversarial Inverse Reinforcement Learning. - Henrik Radtke; Henrik Bey; Moritz Sackmann; Torsten Schön (IV, 2023)

Exploiting GAN Capacity to Generate Synthetic Automotive Radar Data. - Mauren Louise Sguario C. Andrade; Matheus Velloso Nogueira; Eduardo Candioto Fidelis; Luiz Henrique Aguiar Campos; Pietro Lo Presti Campos; Torsten Schön; Lester de Abreu Faria (VISIGRAPP (4: VISAPP), 2023)

Generation of Realistic Synthetic Raw Radar Data for Automated Driving Applications using Generative Adversarial Networks. - Eduardo Candioto Fidelis; Fabio Reway; Herick Y. S. Ribeiro; Pietro Lo Presti Campos; Werner Huber; Christian Icking; Lester de Abreu Faria; Torsten Schön (CoRR, 2023)

Unlocking Past Information: Temporal Embeddings in Cooperative Bird's Eye View Prediction. - Dominik Rößle; Jeremias Gerner; Klaus Bogenberger; Daniel Cremers; Stefanie Schmidtner; Torsten Schön (IV, 2024)

Gaussian-Based and Outside-the-Box Runtime Monitoring Join Forces. - Vahid Hashemi; Jan Kretínský; Sabine Rieder; Torsten Schön; Jan Vorhoff (RV, 2024)

Environment Setup and Model Benchmark of the MuFoRa Dataset. - Islam Fadl; Torsten Schön; Valentino Behret; Thomas Brandmeier; Frank Palme; Thomas Helmer (VISIGRAPP (3): VISAPP, 2025)

Machine Learning Models for Soil Parameter Prediction Based on Satellite, Weather, Clay and Yield Data. - Calvin Kammerlander; Viola Kolb; Marinus Luegmair; Lou Scheermann; Maximilian Schmailzl; Marco Seufert; Jiayun Zhang; Denis Dalic; Torsten Schön (CoRR, 2025)

Advancing Robustness in Deep Reinforcement Learning with an Ensemble Defense Approach. - Adithya Mohan; Dominik Rößle; Daniel Cremers; Torsten Schön (CoRR, 2025)