Lars Rosenbaum

33 papers A* 1A 2B 2C 3Journal 21Unranked 3

Year	Rank	Type	Title / Venue / Authors
2023	A*	`conf`	Unscented Autoencoder. ICML Faris Janjos, Lars Rosenbaum, Maxim Dolgov, J. Marius Zoellner
2023	J	`jnl`	Unscented Autoencoder. CoRR Faris Janjos, Lars Rosenbaum, Maxim Dolgov, J. Marius Zöllner
2022	A	`conf`	DeepFusion: A Robust and Modular 3D Object Detector for Lidars, Cameras and Radars. IROS Florian Drews, Di Feng, Florian Faion, Lars Rosenbaum, Michael Ulrich, Claudius Gläser
2022	J	`jnl`	DeepFusion: A Robust and Modular 3D Object Detector for Lidars, Cameras and Radars. CoRR Florian Drews, Di Feng, Florian Faion, Lars Rosenbaum, Michael Ulrich, Claudius Gläser
2022	J	`jnl`	Labels are Not Perfect: Inferring Spatial Uncertainty in Object Detection. IEEE Trans. Intell. Transp. Syst. Di Feng, Zining Wang, Yiyang Zhou, Lars Rosenbaum, Fabian Timm, Klaus Dietmayer, Masayoshi Tomizuka, Wei Zhan
2021	J	`jnl`	Deep Multi-Modal Object Detection and Semantic Segmentation for Autonomous Driving: Datasets, Methods, and Challenges. IEEE Trans. Intell. Transp. Syst. Di Feng, Christian Haase-Schütz, Lars Rosenbaum, Heinz Hertlein, Claudius Gläser, Fabian Timm, Werner Wiesbeck, Klaus Dietmayer
2020	A	`conf`	Inferring Spatial Uncertainty in Object Detection. IROS Zining Wang, Di Feng, Yiyang Zhou, Lars Rosenbaum, Fabian Timm, Klaus Dietmayer, Masayoshi Tomizuka, Wei Zhan
2020	J	`jnl`	Inferring Spatial Uncertainty in Object Detection. CoRR Zining Wang, Di Feng, Yiyang Zhou, Wei Zhan, Lars Rosenbaum, Fabian Timm, Klaus Dietmayer, Masayoshi Tomizuka
2020	J	`jnl`	Labels Are Not Perfect: Improving Probabilistic Object Detection via Label Uncertainty. CoRR Di Feng, Lars Rosenbaum, Fabian Timm, Klaus Dietmayer
2020	J	`jnl`	Labels Are Not Perfect: Inferring Spatial Uncertainty in Object Detection. CoRR Di Feng, Zining Wang, Yiyang Zhou, Lars Rosenbaum, Fabian Timm, Klaus Dietmayer, Masayoshi Tomizuka, Wei Zhan
2020	C	`conf`	Leveraging Uncertainties for Deep Multi-modal Object Detection in Autonomous Driving. IV Di Feng, Yifan Cao, Lars Rosenbaum, Fabian Timm, Klaus Dietmayer
2020	J	`jnl`	Leveraging Uncertainties for Deep Multi-modal Object Detection in Autonomous Driving. CoRR Di Feng, Yifan Cao, Lars Rosenbaum, Fabian Timm, Klaus Dietmayer
2019	J	`jnl`	Can We Trust You? On Calibration of a Probabilistic Object Detector for Autonomous Driving. CoRR Di Feng, Lars Rosenbaum, Claudius Gläser, Fabian Timm, Klaus Dietmayer
2019	C	`conf`	Deep Active Learning for Efficient Training of a LiDAR 3D Object Detector. IV Di Feng, Xiao Wei, Lars Rosenbaum, Atsuto Maki, Klaus Dietmayer
2019	J	`jnl`	Deep Active Learning for Efficient Training of a LiDAR 3D Object Detector. CoRR Di Feng, Xiao Wei, Lars Rosenbaum, Atsuto Maki, Klaus Dietmayer
2019	J	`jnl`	Deep Multi-modal Object Detection and Semantic Segmentation for Autonomous Driving: Datasets, Methods, and Challenges. CoRR Di Feng, Christian Haase-Schütz, Lars Rosenbaum, Heinz Hertlein, Fabian Duffhauss, Claudius Gläser, Werner Wiesbeck, Klaus Dietmayer
2019	J	`jnl`	Learning Multimodal Fixed-Point Weights using Gradient Descent. CoRR Lukas Enderich, Fabian Timm, Lars Rosenbaum, Wolfram Burgard
2019	B	`conf`	Learning multimodal fixed-point weights using gradient descent. ESANN Lukas Enderich, Fabian Timm, Lars Rosenbaum, Wolfram Burgard
2019	C	`conf`	Leveraging Heteroscedastic Aleatoric Uncertainties for Robust Real-Time LiDAR 3D Object Detection. IV Di Feng, Lars Rosenbaum, Fabian Timm, Klaus Dietmayer
2018	J	`jnl`	Leveraging Heteroscedastic Aleatoric Uncertainties for Robust Real-Time LiDAR 3D Object Detection. CoRR Di Feng, Lars Rosenbaum, Fabian Timm, Klaus Dietmayer
2018	—	`conf`	Towards Safe Autonomous Driving: Capture Uncertainty in the Deep Neural Network For Lidar 3D Vehicle Detection. ITSC Di Feng, Lars Rosenbaum, Klaus Dietmayer
2018	J	`jnl`	Towards Safe Autonomous Driving: Capture Uncertainty in the Deep Neural Network For Lidar 3D Vehicle Detection. CoRR Di Feng, Lars Rosenbaum, Klaus Dietmayer
2015	J	`jnl`	A ranking method for the concurrent learning of compounds with various activity profiles. J. Cheminformatics Alexander Dörr, Lars Rosenbaum, Andreas Zell
2014	—	`—`	Interpretable Machine Learning Models for Mining Chemical Databases. Lars Rosenbaum
2013	J	`jnl`	Inferring multi-target QSAR models with taxonomy-based multi-task learning. J. Cheminformatics Lars Rosenbaum, Alexander Dörr, Matthias R. Bauer, Frank M. Boeckler, Andreas Zell
2013	J	`jnl`	Optimization and visualization of the edge weights in optimal assignment methods for virtual screening. BioData Min. Lars Rosenbaum, Andreas Jahn, Alexander Dörr, Andreas Zell
2012	—	`conf`	Optimizing the Edge Weights in Optimal Assignment Methods for Virtual Screening with Particle Swarm Optimization. EvoBIO Lars Rosenbaum, Andreas Jahn, Andreas Zell
2011	J	`jnl`	4D Flexible Atom-Pairs: An efficient probabilistic conformational space comparison for ligand-based virtual screening. J. Cheminformatics Andreas Jahn, Lars Rosenbaum, Georg Hinselmann, Andreas Zell
2011	—	`conf`	Approximation of Graph Kernel Similarities for Chemical Graphs by Kernel Principal Component Analysis. EvoBio Georg Hinselmann, Andreas Jahn, Nikolas Fechner, Lars Rosenbaum, Andreas Zell
2011	B	`conf`	Fast Data Mining with Sparse Chemical Graph Fingerprints by Estimating the Probability of Unique Patterns. ESANN Georg Hinselmann, Lars Rosenbaum, Andreas Jahn, Andreas Zell
2011	J	`jnl`	Interpreting linear support vector machine models with heat map molecule coloring. J. Cheminformatics Lars Rosenbaum, Georg Hinselmann, Andreas Jahn, Andreas Zell
2011	J	`jnl`	Large-Scale Learning of Structure-Activity Relationships Using a Linear Support Vector Machine and Problem-Specific Metrics. J. Chem. Inf. Model. Georg Hinselmann, Lars Rosenbaum, Andreas Jahn, Nikolas Fechner, Claude Ostermann, Andreas Zell
2011	J	`jnl`	jCompoundMapper: An open source Java library and command-line tool for chemical fingerprints. J. Cheminformatics Georg Hinselmann, Lars Rosenbaum, Andreas Jahn, Nikolas Fechner, Andreas Zell