High-Speed Collision Avoidance using Deep Reinforcement Learning and Domain Randomization for Autonomous Vehicles. - Georgios D. Kontes; Daniel D. Scherer; Tim Nisslbeck; Janina Fischer; Christopher Mutschler (ITSC, 2020)

Can You Trust Your Autonomous Car? Interpretable and Verifiably Safe Reinforcement Learning. - Lukas M. Schmidt; Georgios D. Kontes; Axel Plinge; Christopher Mutschler (IV, 2021)

Driver Dojo: A Benchmark for Generalizable Reinforcement Learning for Autonomous Driving. - Sebastian Rietsch; Shih-Yuan Huang; Georgios D. Kontes; Axel Plinge; Christopher Mutschler (CoRR, 2022)

Efficient Beam Search for Initial Access Using Collaborative Filtering. - George Yammine; Georgios D. Kontes; Norbert Franke; Axel Plinge; Christopher Mutschler (WCNC, 2023)

Augmented Random Search for Multi-Objective Bayesian Optimization of Neural Networks. - Mark Deutel; Georgios D. Kontes; Christopher Mutschler; Jürgen Teich (CoRR, 2023)

C-MCTS: Safe Planning with Monte Carlo Tree Search. - Dinesh Parthasarathy; Georgios D. Kontes; Axel Plinge; Christopher Mutschler (CoRR, 2023)

Benchmarking Quantum Reinforcement Learning. - Nico Meyer; Christian Ufrecht; George Yammine; Georgios D. Kontes; Christopher Mutschler; Daniel D. Scherer (CoRR, 2025)

Position Paper: Rethinking AI/ML for Air Interface in Wireless Networks. - Georgios D. Kontes; Diomidis S. Michalopoulos; Birendra Ghimire; Christopher Mutschler (CoRR, 2025)