Michael Botsch

Publication Activity (10 Years)

Years Active: 2007-2024
Publications (10 Years): 62

Top Topics

Diffusion Models

Vehicle Trajectory

Autonomous Vehicles

Top Venues

Publications

Alexander Fertig, Lakshman Balasubramanian, Michael Botsch
Clustering and Anomaly Detection in Embedding Spaces for the Validation of Automotive Sensors. IV (2024)
Karthikeyan Chandra Sekaran, Lakshman Balasubramanian, Michael Botsch, Wolfgang Utschick
Open-Set Object Detection for the Identification and Localization of Dissimilar Novel Classes by means of Infrastructure Sensors. IV (2024)
Marion Neumeier, Sebastian Dorn, Michael Botsch, Wolfgang Utschick
Reliable Trajectory Prediction and Uncertainty Quantification with Conditioned Diffusion Models. CoRR (2024)
Lakshman Balasubramanian, Jonas Wurst, Robin Egolf, Michael Botsch, Wolfgang Utschick, Ke Deng
SceneDiffusion: Conditioned Latent Diffusion Models for Traffic Scene Prediction. ITSC (2023)
Marion Neumeier, Andreas Tollkühn, Sebastian Dorn, Michael Botsch, Wolfgang Utschick
Optimization and Interpretability of Graph Attention Networks for Small Sparse Graph Structures in Automotive Applications. IV (2023)
Marion Neumeier, Andreas Tollkühn, Michael Botsch, Wolfgang Utschick
A Multidimensional Graph Fourier Transformation Neural Network for Vehicle Trajectory Prediction. CoRR (2023)
Marion Neumeier, Sebastian Dorn, Michael Botsch, Wolfgang Utschick
Prediction and Interpretation of Vehicle Trajectories in the Graph Spectral Domain. CoRR (2023)
Marion Neumeier, Andreas Tollkühn, Sebastian Dorn, Michael Botsch, Wolfgang Utschick
Gradient Derivation for Learnable Parameters in Graph Attention Networks. CoRR (2023)
Marion Neumeier, Andreas Tollkühn, Sebastian Dorn, Michael Botsch, Wolfgang Utschick
Optimization and Interpretability of Graph Attention Networks for Small Sparse Graph Structures in Automotive Applications. CoRR (2023)
Marion Neumeier, Sebastian Dorn, Michael Botsch, Wolfgang Utschick
Prediction and Interpretation of Vehicle Trajectories in the Graph Spectral Domain. ITSC (2023)
Lakshman Balasubramanian, Jonas Wurst, Michael Botsch, Ke Deng
Open-World Learning for Traffic Scenarios Categorisation. IEEE Trans. Intell. Veh. 8 (5) (2023)
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
Data Collection and Safety Use Cases in Smart Infrastructures. AutomotiveUI (Adjunct Proceedings) (2023)
Karthikeyan Chandra Sekaran, Lakshman Balasubramanian, Michael Botsch, Wolfgang Utschick
Metric Learning Based Class Specific Experts for Open-Set Recognition of Traffic Participants in Urban Areas Using Infrastructure Sensors. IV (2023)
Parthasarathy Nadarajan, Michael Botsch, Sebastian Sardiña
Continuous Probabilistic Motion Prediction Based on Latent Space Interpolation. ITSC (2023)
Alberto Flores Fernández, Eduardo Sánchez Morales, Michael Botsch, Christian Facchi, Andrés García Higuera
Generation of Correction Data for Autonomous Driving by Means of Machine Learning and On-Board Diagnostics. Sensors 23 (1) (2023)
Friedrich Kruber, Eduardo Sánchez Morales, Robin Egolf, Jonas Wurst, Samarjit Chakraborty, Michael Botsch
Micro- and Macroscopic Road Traffic Analysis using Drone Image Data. Leibniz Trans. Embed. Syst. 8 (1) (2022)
Tim Elter, Tobias Dirndorfer, Michael Botsch, Wolfgang Utschick
Interaction-aware Prediction of Occupancy Regions based on a POMDP Framework. ITSC (2022)
Jonas Wurst, Lakshman Balasubramanian, Michael Botsch, Wolfgang Utschick
Expert-LaSTS: Expert-Knowledge Guided Latent Space for Traffic Scenarios. IV (2022)
Lakshman Balasubramanian, Jonas Wurst, Robin Egolf, Michael Botsch, Wolfgang Utschick, Ke Deng
ExAgt: Expert-guided Augmentation for Representation Learning of Traffic Scenarios. ITSC (2022)
Marion Neumeier, Andreas Tollkühn, Michael Botsch, Wolfgang Utschick
A Multidimensional Graph Fourier Transformation Neural Network for Vehicle Trajectory Prediction. ITSC (2022)
Jonas Wurst, Lakshman Balasubramanian, Michael Botsch, Wolfgang Utschick
Expert-LaSTS: Expert-Knowledge Guided Latent Space for Traffic Scenarios. CoRR (2022)
Alberto Flores Fernández, Jonas Wurst, Eduardo Sánchez Morales, Michael Botsch, Christian Facchi, Andrés García Higuera
Probabilistic Traffic Motion Labeling for Multi-Modal Vehicle Route Prediction. Sensors 22 (12) (2022)
Lakshman Balasubramanian, Jonas Wurst, Robin Egolf, Michael Botsch, Wolfgang Utschick, Ke Deng
ExAgt: Expert-guided Augmentation for Representation Learning of Traffic Scenarios. CoRR (2022)
Lakshman Balasubramanian, Jonas Wurst, Michael Botsch, Ke Deng
Traffic Scenario Clustering by Iterative Optimisation of Self-Supervised Networks Using a Random Forest Activation Pattern Similarity. CoRR (2021)
Eduardo Sánchez Morales, Julian Dauth, Bertold Huber, Andrés García Higuera, Michael Botsch
High Precision Outdoor and Indoor Reference State Estimation for Testing Autonomous Vehicles. Sensors 21 (4) (2021)
Lakshman Balasubramanian, Friedrich Kruber, Michael Botsch, Ke Deng
Open-Set Recognition based on the Combination of Deep Learning and Ensemble Method for Detecting Unknown Traffic Scenarios. IV (2021)
Jonas Wurst, Lakshman Balasubramanian, Michael Botsch, Wolfgang Utschick
Novelty Detection and Analysis of Traffic Scenario Infrastructures in the Latent Space of a Vision Transformer-Based Triplet Autoencoder. IV (2021)
Lakshman Balasubramanian, Jonas Wurst, Michael Botsch, Ke Deng
Traffic Scenario Clustering by Iterative Optimisation of Self-Supervised Networks Using a Random Forest Activation Pattern Similarity. IV (2021)
Marion Neumeier, Andreas Tollkühn, Thomas Berberich, Michael Botsch
Variational Autoencoder-Based Vehicle Trajectory Prediction with an Interpretable Latent Space. CoRR (2021)
Marion Neumeier, Michael Botsch, Andreas Tollkühn, Thomas Berberich
Variational Autoencoder-Based Vehicle Trajectory Prediction with an Interpretable Latent Space. ITSC (2021)
Lakshman Balasubramanian, Friedrich Kruber, Michael Botsch, Ke Deng
Open-set Recognition based on the Combination of Deep Learning and Ensemble Method for Detecting Unknown Traffic Scenarios. CoRR (2021)
Jonas Wurst, Lakshman Balasubramanian, Michael Botsch, Wolfgang Utschick
Novelty Detection and Analysis of Traffic Scenario Infrastructures in the Latent Space of a Vision Transformer-Based Triplet Autoencoder. CoRR (2021)
Oliver Gallitz, Oliver De Candido, Michael Botsch, Wolfgang Utschick
Interpretable Early Prediction of Lane Changes Using a Constrained Neural Network Architecture. ITSC (2021)
Friedrich Kruber, Jonas Wurst, Michael Botsch
An Unsupervised Random Forest Clustering Technique for Automatic Traffic Scenario Categorization. CoRR (2020)
Jonas Wurst, Alberto Flores Fernández, Michael Botsch, Wolfgang Utschick
An Entropy Based Outlier Score and its Application to Novelty Detection for Road Infrastructure Images. CoRR (2020)
Oliver Gallitz, Oliver De Candido, Michael Botsch, Ron Melz, Wolfgang Utschick
Interpretable Machine Learning Structure for an Early Prediction of Lane Changes. ICANN (1) (2020)
Eduardo Sánchez Morales, Richard Membarth, Andreas Gaull, Philipp Slusallek, Tobias Dirndorfer, Alexander Kammenhuber, Christoph Lauer, Michael Botsch
Parallel Multi-Hypothesis Algorithm for Criticality Estimation in Traffic and Collision Avoidance. CoRR (2020)
Jonas Wurst, Alberto Flores Fernández, Michael Botsch, Wolfgang Utschick
An Entropy Based Outlier Score and its Application to Novelty Detection for Road Infrastructure Images. IV (2020)
Friedrich Kruber, Eduardo Sánchez Morales, Samarjit Chakraborty, Michael Botsch
Vehicle Position Estimation with Aerial Imagery from Unmanned Aerial Vehicles. IV (2020)
Friedrich Kruber, Eduardo Sánchez Morales, Samarjit Chakraborty, Michael Botsch
Vehicle Position Estimation with Aerial Imagery from Unmanned Aerial Vehicles. CoRR (2020)
Friedrich Kruber, Jonas Wurst, Eduardo Sánchez Morales, Samarjit Chakraborty, Michael Botsch
Unsupervised and Supervised Learning with the Random Forest Algorithm for Traffic Scenario Clustering and Classification. CoRR (2020)
Oliver De Candido, Michael Koller, Oliver Gallitz, Ron Melz, Michael Botsch, Wolfgang Utschick
Towards Feature Validation in Time to Lane Change Classification using Deep Neural Networks. ITSC (2020)
Eduardo Sánchez Morales, Michael Botsch, Bertold Huber, Andrés García Higuera
High precision indoor positioning by means of LiDAR. CoRR (2020)
Eduardo Sánchez Morales, Friedrich Kruber, Michael Botsch, Bertold Huber, Andrés García Higuera
Accuracy Characterization of the Vehicle State Estimation from Aerial Imagery. IV (2020)
Eduardo Sánchez Morales, Michael Botsch, Bertold Huber, Andrés García Higuera
High Precision Indoor Navigation for Autonomous Vehicles. CoRR (2020)
Friedrich Kruber, Jonas Wurst, Eduardo Sánchez Morales, Samarjit Chakraborty, Michael Botsch
Unsupervised and Supervised Learning with the Random Forest Algorithm for Traffic Scenario Clustering and Classification. IV (2019)
Oliver Gallitz, Oliver De Candido, Michael Botsch, Wolfgang Utschick
Interpretable Feature Generation using Deep Neural Networks and its Application to Lane Change Detection. ITSC (2019)
Eduardo Sánchez Morales, Michael Botsch, Bertold Huber, Andrés García Higuera
High Precision Indoor Navigation for Autonomous Vehicles. IPIN (2019)
Amit Chaulwar, Hussein Al-Hashimi, Michael Botsch, Wolfgang Utschick
Efficient Hybrid Machine Learning Algorithm for Trajectory Planning in Critical Traffic-Scenarios. ICITE (2019)
Eduardo Sánchez Morales, Richard Membarth, Andreas Gaull, Philipp Slusallek, Tobias Dirndorfer, Alexander Kammenhuber, Christoph Lauer, Michael Botsch
Parallel Multi-Hypothesis Algorithm for Criticality Estimation in Traffic and Collision Avoidance. IV (2019)
Amit Chaulwar, Michael Botsch, Wolfgang Utschick
Generation of Reference Trajectories for Safe Trajectory Planning. ICANN (1) (2018)
Marcus Müller, Xing Longl, Michael Botsch, Dennis Böhmländer, Wolfgang Utschick
Real-Time Crash Severity Estimation with Machine Learning and 2D Mass-Spring-Damper Model. ITSC (2018)
Friedrich Kruber, Jonas Wurst, Michael Botsch
An Unsupervised Random Forest Clustering Technique for Automatic Traffic Scenario Categorization. ITSC (2018)
Valentín Cañas, Eduardo Sánchez Morales, Michael Botsch, Andrés García
Wireless Communication System for the Validation of Autonomous Driving Functions on Full-Scale Vehicles. ICVES (2018)
Gennaro Notomista, Michael Botsch
A Machine Learning Approach for the Segmentation of Driving Maneuvers and its Application in Autonomous Parking. J. Artif. Intell. Soft Comput. Res. 7 (4) (2017)
Parthasarathy Nadarajan, Michael Botsch, Sebastian Sardiña
Predicted-occupancy grids for vehicle safety applications based on autoencoders and the Random Forest algorithm. IJCNN (2017)
Amit Chaulwar, Michael Botsch, Wolfgang Utschick
A machine learning based biased-sampling approach for planning safe trajectories in complex, dynamic traffic-scenarios. Intelligent Vehicles Symposium (2017)
Marcus Müller, Parthasarathy Nadarajan, Michael Botsch, Wolfgang Utschick, Dennis Böhmländer, Stefan Katzenbogen
A statistical learning approach for estimating the reliability of crash severity predictions. ITSC (2016)
Parthasarathy Nadarajan, Michael Botsch
Probability estimation for Predicted-Occupancy Grids in vehicle safety applications based on machine learning. Intelligent Vehicles Symposium (2016)
Amit Chaulwar, Michael Botsch, Wolfgang Utschick
A Hybrid Machine Learning Approach for Planning Safe Trajectories in Complex Traffic-Scenarios. ICMLA (2016)
Gennaro Notomista, Michael Botsch
Maneuver segmentation for autonomous parking based on ensemble learning. IJCNN (2015)
Stephan Herrmann, Wolfgang Utschick, Michael Botsch, Frank Keck
Supervised Learning via Optimal Control Labeling for Criticality Classification in Vehicle Active Safety. ITSC (2015)
Michael Reichel, Michael Botsch, Robert Rauschecker, Karl-Heinz Siedersberger, Markus Maurer
Situation aspect modelling and classification using the Scenario Based Random Forest algorithm for convoy merging situations. ITSC (2010)
Michael Botsch, Christoph Lauer
Complexity reduction using the Random Forest classifier in a collision detection algorithm. Intelligent Vehicles Symposium (2010)
Michael Botsch, Josef A. Nossek
Construction of interpretable Radial Basis Function classifiers based on the Random Forest kernel. IJCNN (2008)
Michael Botsch, Josef A. Nossek
Feature Selection for Change Detection in Multivariate Time-Series. CIDM (2007)