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Daniel Bogdoll — most-cited papers & profile · Robotics
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Daniel Bogdoll
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Most-cited papers
Real-World On-Vehicle Evaluation of Embedding-Based Anomaly Detection
2026
Beyond Scalar Rewards: Distributional Reinforcement Learning with Preordered Objectives for Safe and Reliable Autonomous Driving
2026
Towards Sensor Data Abstraction of Autonomous Vehicle Perception Systems
2021
Compressing Sensor Data for Remote Assistance of Autonomous Vehicles using Deep Generative Models
2021
Ad-datasets: a meta-collection of data sets for autonomous driving
2022
Anomaly Detection in Autonomous Driving: A Survey
2022
Knowledge Augmented Machine Learning with Applications in Autonomous Driving: A Survey
2022
Experiments on Anomaly Detection in Autonomous Driving by Forward-Backward Style Transfers
2022
DLCSS: Dynamic Longest Common Subsequences
2022
Impact, Attention, Influence: Early Assessment of Autonomous Driving Datasets
2023
From Model-Based to Data-Driven Simulation: Challenges and Trends in Autonomous Driving
2023
Exploring the Potential of World Models for Anomaly Detection in Autonomous Driving
2023
Conditioning Latent-Space Clusters for Real-World Anomaly Classification
2023
MUVO: A Multimodal Generative World Model for Autonomous Driving with Geometric Representations
2023
Informed Reinforcement Learning for Situation-Aware Traffic Rule Exceptions
2024
Top co-authors
J. Marius Z\"ollner
· 15
Tim Joseph
· 6
Svetlana Pavlitska
· 5
Ahmed Abouelazm
· 3
Felix Schreyer
· 2
Helen Gremmelmaier
· 2
Jonas Rauch
· 2
Maximilian Nitsche
· 2
Moritz Nekolla
· 2
Yitian Yang
· 2
Abhishek Vivekanandan
· 1
Adrian Paschke
· 1
Topics
cs.RO
cs.CV
cs.LG
cs.AI
eess.SP
cs.DL