Using case-based reasoning for autonomous vehicle guidance. - Stefan Vacek; Tobias Gindele; Johann Marius Zöllner; Rüdiger Dillmann (IROS, 2007)

Team AnnieWAY's Autonomous System. - Christoph Stiller; Sören Kammel; Benjamin Pitzer; Julius Ziegler; Moritz Werling; Tobias Gindele; Daniel Jagszent (RobVis, 2008)

Team AnnieWAY's autonomous system for the 2007 DARPA Urban Challenge. - Sören Kammel; Julius Ziegler; Benjamin Pitzer; Moritz Werling; Tobias Gindele; Daniel Jagszent; Joachim Schröder; Michael Thuy; Matthias Goebl; Felix von Hundelshausen; Oliver Pink; Christian Frese; et al. (J. Field Robotics, 2008)

Probabilistisches Belegtheitsfilter zur Schätzung dynamischer Umgebungen unter Verwendung multipler Bewegungsmodelle. - Sebastian Brechtel; Tobias Gindele; Jan Vogelgesang; Rüdiger Dillmann (AMS, 2009)

Dynamic Bayesian Network Library - Ein C++ Framework für Berechnungen auf dynamischen Bayes'schen Netzen. - Ralf Kohlhaas; Ferdinand Szekeresch; Tobias Gindele; Rüdiger Dillmann (AMS, 2009)

Team AnnieWAY's Autonomous System for the DARPA Urban Challenge 2007. - Sören Kammel; Julius Ziegler; Benjamin Pitzer; Moritz Werling; Tobias Gindele; Daniel Jagszent; Joachim Schröder; Michael Thuy; Matthias Goebl; Felix von Hundelshausen; Oliver Pink; Christian Frese; et al. (The DARPA Urban Challenge, 2009)

Recursive importance sampling for efficient grid-based occupancy filtering in dynamic environments. - Sebastian Brechtel; Tobias Gindele; Rüdiger Dillmann (ICRA, 2010)

A probabilistic model for estimating driver behaviors and vehicle trajectories in traffic environments. - Tobias Gindele; Sebastian Brechtel; Rüdiger Dillmann (ITSC, 2010)

Probabilistic MDP-behavior planning for cars. - Sebastian Brechtel; Tobias Gindele; Rüdiger Dillmann (ITSC, 2011)

Solving Continuous POMDPs: Value Iteration with Incremental Learning of an Efficient Space Representation. - Sebastian Brechtel; Tobias Gindele; Rüdiger Dillmann (ICML (3), 2013)

Learning context sensitive behavior models from observations for predicting traffic situations. - Tobias Gindele; Sebastian Brechtel; Rüdiger Dillmann (ITSC, 2013)

Probabilistic decision-making under uncertainty for autonomous driving using continuous POMDPs. - Sebastian Brechtel; Tobias Gindele; Rüdiger Dillmann (ITSC, 2014)

Learning Behavior Models for Interpreting and Predicting Traffic Situations. - Tobias Gindele (2014)

Inverse reinforcement learning of behavioral models for online-adapting navigation strategies. - Michael Herman; Volker Fischer 003; Tobias Gindele; Wolfram Burgard (ICRA, 2015)

Learning Driver Behavior Models from Traffic Observations for Decision Making and Planning. - Tobias Gindele; Sebastian Brechtel; Rüdiger Dillmann (IEEE Intell. Transp. Syst. Mag., 2015)

Inverse Reinforcement Learning with Simultaneous Estimation of Rewards and Dynamics. - Michael Herman; Tobias Gindele; Jörg Wagner; Felix Schmitt 001; Wolfram Burgard (AISTATS, 2016)

Learning High-Level Navigation Strategies via Inverse Reinforcement Learning: A Comparative Analysis. - Michael Herman; Tobias Gindele; Jörg Wagner; Felix Schmitt 001; Christophe Quignon; Wolfram Burgard (Australasian Conference on Artificial Intelligence, 2016)

Simultaneous estimation of rewards and dynamics from noisy expert demonstrations. - Michael Herman; Tobias Gindele; Jörg Wagner; Felix Schmitt 001; Wolfram Burgard (ESANN, 2016)

Interpretable and Fine-Grained Visual Explanations for Convolutional Neural Networks. - Jörg Wagner; Jan Mathias Köhler; Tobias Gindele; Leon Hetzel; Jakob Thaddäus Wiedemer; Sven Behnke (CVPR, 2019)

MMAU: A Holistic Benchmark of Agent Capabilities Across Diverse Domains. - Guoli Yin; Haoping Bai; Shuang Ma; Feng Nan; Yanchao Sun; Zhaoyang Xu; Shen Ma; Jiarui Lu; Xiang Kong; Aonan Zhang; Dian Ang Yap; Yizhe Zhang 002; et al. (NAACL (Findings), 2025)