Feature Selection for Change Detection in Multivariate Time-Series. - Michael Botsch; Josef A. Nossek (CIDM, 2007)

Construction of interpretable Radial Basis Function classifiers based on the Random Forest kernel. - Michael Botsch; Josef A. Nossek (IJCNN, 2008)

Situation aspect modelling and classification using the Scenario Based Random Forest algorithm for convoy merging situations. - Michael Reichel; Michael Botsch; Robert Rauschecker; Karl-Heinz Siedersberger; Markus Maurer (ITSC, 2010)

Complexity reduction using the Random Forest classifier in a collision detection algorithm. - Michael Botsch; Christoph Lauer (Intelligent Vehicles Symposium, 2010)

Maneuver segmentation for autonomous parking based on ensemble learning. - Gennaro Notomista; Michael Botsch (IJCNN, 2015)

Supervised Learning via Optimal Control Labeling for Criticality Classification in Vehicle Active Safety. - Stephan Herrmann 003; Wolfgang Utschick; Michael Botsch; Frank Keck (ITSC, 2015)

A Hybrid Machine Learning Approach for Planning Safe Trajectories in Complex Traffic-Scenarios. - Amit Chaulwar; Michael Botsch; Wolfgang Utschick (ICMLA, 2016)

A statistical learning approach for estimating the reliability of crash severity predictions. - Marcus Müller 003; Parthasarathy Nadarajan; Michael Botsch; Wolfgang Utschick; Dennis Böhmländer; Stefan Katzenbogen (ITSC, 2016)

Probability estimation for Predicted-Occupancy Grids in vehicle safety applications based on machine learning. - Parthasarathy Nadarajan; Michael Botsch (Intelligent Vehicles Symposium, 2016)

Predicted-occupancy grids for vehicle safety applications based on autoencoders and the Random Forest algorithm. - Parthasarathy Nadarajan; Michael Botsch; Sebastian Sardiña (IJCNN, 2017)

A machine learning based biased-sampling approach for planning safe trajectories in complex, dynamic traffic-scenarios. - Amit Chaulwar; Michael Botsch; Wolfgang Utschick (Intelligent Vehicles Symposium, 2017)

A Machine Learning Approach for the Segmentation of Driving Maneuvers and its Application in Autonomous Parking. - Gennaro Notomista; Michael Botsch (J. Artif. Intell. Soft Comput. Res., 2017)

Generation of Reference Trajectories for Safe Trajectory Planning. - Amit Chaulwar; Michael Botsch; Wolfgang Utschick (ICANN (1), 2018)

Wireless Communication System for the Validation of Autonomous Driving Functions on Full-Scale Vehicles. - Valentín Cañas; Eduardo Sánchez Morales; Michael Botsch; Andrés García 001 (ICVES, 2018)

Real-Time Crash Severity Estimation with Machine Learning and 2D Mass-Spring-Damper Model. - Marcus Müller 003; Xing Longl; Michael Botsch; Dennis Böhmländer; Wolfgang Utschick (ITSC, 2018)

An Unsupervised Random Forest Clustering Technique for Automatic Traffic Scenario Categorization. - Friedrich Kruber; Jonas Wurst; Michael Botsch (ITSC, 2018)

Efficient Hybrid Machine Learning Algorithm for Trajectory Planning in Critical Traffic-Scenarios. - Amit Chaulwar; Hussein Al-Hashimi; Michael Botsch; Wolfgang Utschick (ICITE, 2019)

High Precision Indoor Navigation for Autonomous Vehicles. - Eduardo Sánchez Morales; Michael Botsch; Bertold Huber; Andrés García Higuera (IPIN, 2019)

Interpretable Feature Generation using Deep Neural Networks and its Application to Lane Change Detection. - Oliver Gallitz; Oliver De Candido; Michael Botsch; Wolfgang Utschick (ITSC, 2019)

Unsupervised and Supervised Learning with the Random Forest Algorithm for Traffic Scenario Clustering and Classification. - Friedrich Kruber; Jonas Wurst; Eduardo Sánchez Morales; Samarjit Chakraborty; Michael Botsch (IV, 2019)

Parallel Multi-Hypothesis Algorithm for Criticality Estimation in Traffic and Collision Avoidance. - Eduardo Sánchez Morales; Richard Membarth; Andreas Gaull; Philipp Slusallek; Tobias Dirndorfer; Alexander Kammenhuber; Christoph Lauer; Michael Botsch (IV, 2019)

Interpretable Machine Learning Structure for an Early Prediction of Lane Changes. - Oliver Gallitz; Oliver De Candido; Michael Botsch; Ron Melz; Wolfgang Utschick (ICANN (1), 2020)

Towards Feature Validation in Time to Lane Change Classification using Deep Neural Networks. - Oliver De Candido; Michael Koller 001; Oliver Gallitz; Ron Melz; Michael Botsch; Wolfgang Utschick (ITSC, 2020)

Vehicle Position Estimation with Aerial Imagery from Unmanned Aerial Vehicles. - Friedrich Kruber; Eduardo Sánchez Morales; Samarjit Chakraborty; Michael Botsch (IV, 2020)

Accuracy Characterization of the Vehicle State Estimation from Aerial Imagery. - Eduardo Sánchez Morales; Friedrich Kruber; Michael Botsch; Bertold Huber; Andrés García Higuera (IV, 2020)

An Entropy Based Outlier Score and its Application to Novelty Detection for Road Infrastructure Images. - Jonas Wurst; Alberto Flores Fernández; Michael Botsch; Wolfgang Utschick (IV, 2020)

High precision indoor positioning by means of LiDAR. - Eduardo Sánchez Morales; Michael Botsch; Bertold Huber; Andrés García Higuera (CoRR, 2020)

Interpretable Early Prediction of Lane Changes Using a Constrained Neural Network Architecture. - Oliver Gallitz; Oliver De Candido; Michael Botsch; Wolfgang Utschick (ITSC, 2021)

Variational Autoencoder-Based Vehicle Trajectory Prediction with an Interpretable Latent Space. - Marion Neumeier; Michael Botsch; Andreas Tollkühn; Thomas Berberich (ITSC, 2021)

Open-Set Recognition based on the Combination of Deep Learning and Ensemble Method for Detecting Unknown Traffic Scenarios. - Lakshman Balasubramanian; Friedrich Kruber; Michael Botsch; Ke Deng (IV, 2021)

Traffic Scenario Clustering by Iterative Optimisation of Self-Supervised Networks Using a Random Forest Activation Pattern Similarity. - Lakshman Balasubramanian; Jonas Wurst; Michael Botsch; Ke Deng (IV, 2021)

Novelty Detection and Analysis of Traffic Scenario Infrastructures in the Latent Space of a Vision Transformer-Based Triplet Autoencoder. - Jonas Wurst; Lakshman Balasubramanian; Michael Botsch; Wolfgang Utschick (IV, 2021)

High Precision Outdoor and Indoor Reference State Estimation for Testing Autonomous Vehicles. - Eduardo Sánchez Morales; Julian Dauth; Bertold Huber; Andrés García Higuera; Michael Botsch (Sensors, 2021)

ExAgt: Expert-guided Augmentation for Representation Learning of Traffic Scenarios. - Lakshman Balasubramanian; Jonas Wurst; Robin Egolf; Michael Botsch; Wolfgang Utschick; Ke Deng (ITSC, 2022)

Interaction-aware Prediction of Occupancy Regions based on a POMDP Framework. - Tim Elter; Tobias Dirndorfer; Michael Botsch; Wolfgang Utschick (ITSC, 2022)

A Multidimensional Graph Fourier Transformation Neural Network for Vehicle Trajectory Prediction. - Marion Neumeier; Andreas Tollkühn; Michael Botsch; Wolfgang Utschick (ITSC, 2022)

Expert-LaSTS: Expert-Knowledge Guided Latent Space for Traffic Scenarios. - Jonas Wurst; Lakshman Balasubramanian; Michael Botsch; Wolfgang Utschick (IV, 2022)

Micro- and Macroscopic Road Traffic Analysis using Drone Image Data. - Friedrich Kruber; Eduardo Sánchez Morales; Robin Egolf; Jonas Wurst; Samarjit Chakraborty; Michael Botsch (Leibniz Trans. Embed. Syst., 2022)

Probabilistic Traffic Motion Labeling for Multi-Modal Vehicle Route Prediction. - Alberto Flores Fernández; Jonas Wurst; Eduardo Sánchez Morales; Michael Botsch; Christian Facchi; Andrés García Higuera (Sensors, 2022)

Data Collection and Safety Use Cases in Smart Infrastructures. - Michael Botsch; Werner Huber; Lakshman Balasubramanian; Alberto Flores Fernández; Markus Geisler; Christian Gudera; Mauricio Rene Morales Gomez; Peter Riegl; Eduardo Sánchez Morales; Karthikeyan Chandra Sekaran (AutomotiveUI (Adjunct Proceedings), 2023)

SceneDiffusion: Conditioned Latent Diffusion Models for Traffic Scene Prediction. - Lakshman Balasubramanian; Jonas Wurst; Robin Egolf; Michael Botsch; Wolfgang Utschick; Ke Deng (ITSC, 2023)

Continuous Probabilistic Motion Prediction Based on Latent Space Interpolation. - Parthasarathy Nadarajan; Michael Botsch; Sebastian Sardiña (ITSC, 2023)

Prediction and Interpretation of Vehicle Trajectories in the Graph Spectral Domain. - Marion Neumeier; Sebastian Dorn; Michael Botsch; Wolfgang Utschick (ITSC, 2023)

Optimization and Interpretability of Graph Attention Networks for Small Sparse Graph Structures in Automotive Applications. - Marion Neumeier; Andreas Tollkühn; Sebastian Dorn; Michael Botsch; Wolfgang Utschick (IV, 2023)

Metric Learning Based Class Specific Experts for Open-Set Recognition of Traffic Participants in Urban Areas Using Infrastructure Sensors. - Karthikeyan Chandra Sekaran; Lakshman Balasubramanian; Michael Botsch; Wolfgang Utschick (IV, 2023)

Gradient Derivation for Learnable Parameters in Graph Attention Networks. - Marion Neumeier; Andreas Tollkühn; Sebastian Dorn; Michael Botsch; Wolfgang Utschick (CoRR, 2023)

Generation of Correction Data for Autonomous Driving by Means of Machine Learning and On-Board Diagnostics. - Alberto Flores Fernández; Eduardo Sánchez Morales; Michael Botsch; Christian Facchi; Andrés García Higuera (Sensors, 2023)

Open-World Learning for Traffic Scenarios Categorisation. - Lakshman Balasubramanian; Jonas Wurst; Michael Botsch; Ke Deng (IEEE Trans. Intell. Veh., 2023)

Reliable Trajectory Prediction and Uncertainty Quantification with Conditioned Diffusion Models. - Marion Neumeier; Sebastian Dorn; Michael Botsch; Wolfgang Utschick (CVPR Workshops, 2024)

Generation of Realistic Traffic Scenarios for Virtual and Real Test Drives Based on a Hybrid Machine Learning Framework. - Peter Riegl; Karthikeyan Chandra Sekaran; Michael Botsch (ICVES, 2024)

Clustering and Anomaly Detection in Embedding Spaces for the Validation of Automotive Sensors. - Alexander Fertig; Lakshman Balasubramanian; Michael Botsch (IV, 2024)

Open-Set Object Detection for the Identification and Localization of Dissimilar Novel Classes by means of Infrastructure Sensors. - Karthikeyan Chandra Sekaran; Lakshman Balasubramanian; Michael Botsch; Wolfgang Utschick (IV, 2024)

Hybrid Machine Learning Model with a Constrained Action Space for Trajectory Prediction. - Alexander Fertig; Lakshman Balasubramanian; Michael Botsch (CoRR, 2025)

Uncertainty-Aware Hybrid Machine Learning in Virtual Sensors for Vehicle Sideslip Angle Estimation. - Abinav Kalyanasundaram; Karthikeyan Chandra Sekaran; Philipp Stauber; Michael Lange 004; Wolfgang Utschick; Michael Botsch (CoRR, 2025)

Assessing the Completeness of Traffic Scenario Categories for Automated Highway Driving Functions via Cluster-based Analysis. - Niklas Roßberg; Marion Neumeier; Sinan Hasirlioglu; Mohamed Essayed Bouzouraa; Michael Botsch (CoRR, 2025)