Fast Data Mining with Sparse Chemical Graph Fingerprints by Estimating the Probability of Unique Patterns. - Georg Hinselmann; Lars Rosenbaum; Andreas Jahn 001; Andreas Zell (ESANN, 2011)

Approximation of Graph Kernel Similarities for Chemical Graphs by Kernel Principal Component Analysis. - Georg Hinselmann; Andreas Jahn 001; Nikolas Fechner; Lars Rosenbaum; Andreas Zell (EvoBio, 2011)

jCompoundMapper: An open source Java library and command-line tool for chemical fingerprints. - Georg Hinselmann; Lars Rosenbaum; Andreas Jahn 001; Nikolas Fechner; Andreas Zell (J. Cheminformatics, 2011)

4D Flexible Atom-Pairs: An efficient probabilistic conformational space comparison for ligand-based virtual screening. - Andreas Jahn 001; Lars Rosenbaum; Georg Hinselmann; Andreas Zell (J. Cheminformatics, 2011)

Interpreting linear support vector machine models with heat map molecule coloring. - Lars Rosenbaum; Georg Hinselmann; Andreas Jahn 001; Andreas Zell (J. Cheminformatics, 2011)

Large-Scale Learning of Structure-Activity Relationships Using a Linear Support Vector Machine and Problem-Specific Metrics. - Georg Hinselmann; Lars Rosenbaum; Andreas Jahn 001; Nikolas Fechner; Claude Ostermann; Andreas Zell (J. Chem. Inf. Model., 2011)

Optimizing the Edge Weights in Optimal Assignment Methods for Virtual Screening with Particle Swarm Optimization. - Lars Rosenbaum; Andreas Jahn 001; Andreas Zell (EvoBIO, 2012)

Optimization and visualization of the edge weights in optimal assignment methods for virtual screening. - Lars Rosenbaum; Andreas Jahn 001; Alexander Dörr; Andreas Zell (BioData Min., 2013)

Inferring multi-target QSAR models with taxonomy-based multi-task learning. - Lars Rosenbaum; Alexander Dörr; Matthias R. Bauer; Frank M. Boeckler; Andreas Zell (J. Cheminformatics, 2013)

Interpretable Machine Learning Models for Mining Chemical Databases. - Lars Rosenbaum (Verlag Dr. Hut, 2014)

A ranking method for the concurrent learning of compounds with various activity profiles. - Alexander Dörr; Lars Rosenbaum; Andreas Zell (J. Cheminformatics, 2015)

Towards Safe Autonomous Driving: Capture Uncertainty in the Deep Neural Network For Lidar 3D Vehicle Detection. - Di Feng; Lars Rosenbaum; Klaus Dietmayer (ITSC, 2018)

Learning multimodal fixed-point weights using gradient descent. - Lukas Enderich; Fabian Timm; Lars Rosenbaum; Wolfram Burgard (ESANN, 2019)

Leveraging Heteroscedastic Aleatoric Uncertainties for Robust Real-Time LiDAR 3D Object Detection. - Di Feng; Lars Rosenbaum; Fabian Timm; Klaus Dietmayer (IV, 2019)

Deep Active Learning for Efficient Training of a LiDAR 3D Object Detector. - Di Feng; Xiao Wei; Lars Rosenbaum; Atsuto Maki; Klaus Dietmayer (IV, 2019)

Deep Multi-modal Object Detection and Semantic Segmentation for Autonomous Driving: Datasets, Methods, and Challenges. - Di Feng; Christian Haase-Schütz; Lars Rosenbaum; Heinz Hertlein; Fabian Duffhauss; Claudius Gläser; Werner Wiesbeck; Klaus Dietmayer (CoRR, 2019)

Can We Trust You? On Calibration of a Probabilistic Object Detector for Autonomous Driving. - Di Feng; Lars Rosenbaum; Claudius Gläser; Fabian Timm; Klaus Dietmayer (CoRR, 2019)

Inferring Spatial Uncertainty in Object Detection. - Zining Wang; Di Feng; Yiyang Zhou; Lars Rosenbaum; Fabian Timm; Klaus Dietmayer; Masayoshi Tomizuka; Wei Zhan (IROS, 2020)

Leveraging Uncertainties for Deep Multi-modal Object Detection in Autonomous Driving. - Di Feng; Yifan Cao; Lars Rosenbaum; Fabian Timm; Klaus Dietmayer (IV, 2020)

Labels Are Not Perfect: Improving Probabilistic Object Detection via Label Uncertainty. - Di Feng; Lars Rosenbaum; Fabian Timm; Klaus Dietmayer (CoRR, 2020)

Deep Multi-Modal Object Detection and Semantic Segmentation for Autonomous Driving: Datasets, Methods, and Challenges. - Di Feng; Christian Haase-Schütz; Lars Rosenbaum; Heinz Hertlein; Claudius Gläser; Fabian Timm; Werner Wiesbeck; Klaus Dietmayer (IEEE Trans. Intell. Transp. Syst., 2021)

DeepFusion: A Robust and Modular 3D Object Detector for Lidars, Cameras and Radars. - Florian Drews; Di Feng; Florian Faion; Lars Rosenbaum; Michael Ulrich; Claudius Gläser (IROS, 2022)

Labels are Not Perfect: Inferring Spatial Uncertainty in Object Detection. - Di Feng; Zining Wang; Yiyang Zhou; Lars Rosenbaum; Fabian Timm; Klaus Dietmayer; Masayoshi Tomizuka; Wei Zhan (IEEE Trans. Intell. Transp. Syst., 2022)

Unscented Autoencoder. - Faris Janjos; Lars Rosenbaum; Maxim Dolgov; J. Marius Zoellner (ICML, 2023)