most citedDriver Dojo: A Benchmark for Generalizable Reinforcement Learning for Autonomous Driving

5 citations · 11 across the 5 of their papers we have counts for

collaborators

5 papers

eess.SP2024

Radio Foundation Models: Pre-training Transformers for 5G-based Indoor Localization

Jonathan Ott, Jonas Pirkl, Maximilian Stahlke +2

Artificial Intelligence (AI)-based radio fingerprinting (FP) outperforms classic localization methods in propagation environments with strong multipath effects. However, the model…

quant-ph20243 cited

Improving Quantum and Classical Decomposition Methods for Vehicle Routing

Laura S. Herzog, Friedrich Wagner, Christian Ufrecht +4

Quantum computing is a promising technology to address combinatorial optimization problems, for example via the quantum approximate optimization algorithm (QAOA). Its potential, ho…

eess.SP20221 cited

Towards Realistic Statistical Channel Models For Positioning: Evaluating the Impact of Early Clusters

Mohammad Alawieh, George Yammine, Ernst Eberlein +5

Physical effects such as reflection, refraction, and diffraction cause a radio signal to arrive from a transmitter to a receiver in multiple replicas that have different amplitude…

eess.SP20222 cited

Complementary Semi-Deterministic Clusters for Realistic Statistical Channel Models for Positioning

Mohammad Alawieh, Ernst Eberlein, Stephan Jäckel +5

Positioning benefits from channel models that capture geometric effects and, in particular, from the signal properties of the first arriving path and the spatial consistency of the…

cs.LG20225 cited

Driver Dojo: A Benchmark for Generalizable Reinforcement Learning for Autonomous Driving

Sebastian Rietsch, Shih-Yuan Huang, Georgios Kontes +2

Reinforcement learning (RL) has shown to reach super human-level performance across a wide range of tasks. However, unlike supervised machine learning, learning strategies that gen…