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ORCIDMarco F. Huber
Person information
- affiliation: University of Stuttgart, Institute of Industrial Manufacturing and Management (IFF), Germany
- affiliation: Fraunhofer Institute for Manufacturing Engineering and Automation (IPA), Stuttgart, Germany
- affiliation (former): USU Software AG, Karlsruhe, Germany
- affiliation (former, PhD 2015): Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
- affiliation (former): AGT International, Darmstadt, Germany
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2020 – today
- 2024
[c86]Ruyu Wang, Sabrina Schmedding, Marco F. Huber:
Improving the Effectiveness of Deep Generative Data. WACV 2024: 4910-4920- [i40]Benjamin Alt, Florian Stöckl, Silvan Müller, Christopher Braun, Julian Raible, Saad Alhasan, Oliver Rettig, Lukas Ringle, Darko Katic, Rainer Jäkel, Michael Beetz, Marcus Strand, Marco F. Huber:
RoboGrind: Intuitive and Interactive Surface Treatment with Industrial Robots. CoRR abs/2402.16542 (2024) - [i39]Fabian Mauthe, Christopher Braun, Julian Raible, Peter Zeiler, Marco F. Huber:
Overview of Publicly Available Degradation Data Sets for Tasks within Prognostics and Health Management. CoRR abs/2403.13694 (2024) - [i38]Benjamin Frész, Elena Dubovitskaya, Danilo Brajovic, Marco F. Huber, Christian Horz:
How should AI decisions be explained? Requirements for Explanations from the Perspective of European Law. CoRR abs/2404.12762 (2024) - [i37]Florenz Graf, Jochen Lindermayr, Birgit Graf, Werner Kraus, Marco F. Huber:
HIPer: A Human-Inspired Scene Perception Model for Multifunctional Mobile Robots. CoRR abs/2404.17791 (2024) - 2023
- [j16]Marc-André Zöller
, Waldemar Titov, Thomas Schlegel, Marco F. Huber:
XAutoML: A Visual Analytics Tool for Understanding and Validating Automated Machine Learning. ACM Trans. Interact. Intell. Syst. 13(4): 28:1-28:39 (2023) - [c85]Philipp Wagner, Xinyang Wu, Marco F. Huber:
Kalman Bayesian Neural Networks for Closed-Form Online Learning. AAAI 2023: 10069-10077 - [c84]Julian Raible, Oliver Rettig, Benjamin Alt, Alper Yaman, Isabelle Gauger, Lorenzo Biasi, Silvan Müller, Darko Katic, Marcus Strand, Marco F. Huber:
Artificial Neural Network Guided Compensation of Nonlinear Payload and Wear Effects for Industrial Robots. CASE 2023: 1-8 - [c83]Patrick Takenaka, Johannes Maucher, Marco F. Huber:
Guiding Video Prediction with Explicit Procedural Knowledge. ICCV (Workshops) 2023: 1076-1084 - [c82]Xinyang Wu, Mohamed El-Shamouty, Christof Nitsche, Marco F. Huber:
Uncertainty-Guided Active Reinforcement Learning with Bayesian Neural Networks. ICRA 2023: 5751-5757 - [c81]Kathrin Leiner, Frederic P. Dollmann, Marco F. Huber, Manuel Geiger, Stefan Leinberger:
Cut Interruption Detection in the Laser Cutting Process Using ROCKET on Audio Signals. INDIN 2023: 1-6 - [c80]Jochen Lindermayr, Çagatay Odabasi, Florian Jordan, Florenz Graf, Lukas Knak, Werner Kraus, Richard Bormann, Marco F. Huber:
IPA-3D1K: A Large Retail 3D Model Dataset for Robot Picking. IROS 2023: 11404-11411 - [c79]Xinyang Wu, Elisabeth Wedernikow, Christof Nitsche, Marco F. Huber:
Towards Optimal Energy Management Strategy for Hybrid Electric Vehicle with Reinforcement Learning. IV 2023: 1-7 - [c78]Marc-André Zöller, Fabian Mauthe, Peter Zeiler, Marius Lindauer, Marco F. Huber:
Automated Machine Learning for Remaining Useful Life Predictions. SMC 2023: 2907-2912 - [c77]Christian Jauch, Timo Leitritz, Marco F. Huber:
Self-Supervised Optimization of Hand Pose Estimation Using Anatomical Features and Iterative Learning. SMC 2023: 4519-4524 - [i36]Ruyu Wang, Sabrina Hoppe, Eduardo Monari, Marco F. Huber:
Defect Transfer GAN: Diverse Defect Synthesis for Data Augmentation. CoRR abs/2302.08366 (2023) - [i35]Jannes Elstner, Raoul G. C. Schönhof, Steffen Tauber, Marco F. Huber:
Optimizing CAD Models with Latent Space Manipulation. CoRR abs/2303.12739 (2023) - [i34]Xinyang Wu, Elisabeth Wedernikow, Christof Nitsche, Marco F. Huber:
Towards Optimal Energy Management Strategy for Hybrid Electric Vehicle with Reinforcement Learning. CoRR abs/2305.12365 (2023) - [i33]Marc-André Zöller, Fabian Mauthe, Peter Zeiler, Marius Lindauer, Marco F. Huber:
Automated Machine Learning for Remaining Useful Life Predictions. CoRR abs/2306.12215 (2023) - [i32]Christian Jauch, Timo Leitritz, Marco F. Huber:
Self-supervised Optimization of Hand Pose Estimation using Anatomical Features and Iterative Learning. CoRR abs/2307.03007 (2023) - [i31]Danilo Brajovic, Niclas Renner, Vincent Philipp Goebels, Philipp Wagner, Benjamin Frész, Martin Biller, Mara Klaeb, Janika Kutz, Jens Neuhüttler, Marco F. Huber:
Model Reporting for Certifiable AI: A Proposal from Merging EU Regulation into AI Development. CoRR abs/2307.11525 (2023) - [i30]Ruyu Wang, Sabrina Schmedding, Marco F. Huber:
Improving the Effectiveness of Deep Generative Data. CoRR abs/2311.03959 (2023) - [i29]Marc-André Zöller, Marius Lindauer, Marco F. Huber:
auto-sktime: Automated Time Series Forecasting. CoRR abs/2312.08528 (2023) - [i28]Danilo Brajovic, Marco F. Huber:
Merging Explainable AI into Automotive Software Development. ERCIM News 2023(134) (2023) - 2022
- [j15]Nadia Burkart, Danilo Brajovic, Marco F. Huber:
Explainable AI: introducing trust and comprehensibility to AI engineering. Autom. 70(9): 787-792 (2022) - [j14]Manjunatha Veerappa, Mathias Anneken, Nadia Burkart, Marco F. Huber:
Validation of XAI explanations for multivariate time series classification in the maritime domain. J. Comput. Sci. 58: 101539 (2022) - [j13]Florenz Graf, Jochen Lindermayr, Çagatay Odabasi, Marco F. Huber:
Toward Holistic Scene Understanding: A Transfer of Human Scene Perception to Mobile Robots. IEEE Robotics Autom. Mag. 29(4): 36-49 (2022) - [c76]Ruyu Wang, Sabrina Hoppe, Eduardo Monari, Marco F. Huber:
Defect Transfer GAN: Diverse Defect Synthesis for Data Augmentation. BMVC 2022: 445 - [c75]Tobias Nagel, Marco F. Huber:
Kalman-Bucy-Informed Neural Network for System Identification. CDC 2022: 1503-1508 - [c74]Mohamed El-Shamouty, Julian Titze, Sitar Kortik, Werner Kraus, Marco F. Huber:
GLIR: A Practical Global-local Integrated Reactive Planner towards Safe Human-Robot Collaboration. ETFA 2022: 1-8 - [c73]Pascal Weller, Fady Aziz, Sherif Abdulatif, Urs Schneider, Marco F. Huber:
A MIMO Radar-based Few-Shot Learning Approach for Human-ID. EUSIPCO 2022: 1796-1800 - [c72]Simeon Brüggenjürgen, Nina Schaaf, Pascal Kerschke, Marco F. Huber:
Mixture of Decision Trees for Interpretable Machine Learning. ICMLA 2022: 1175-1182 - [c71]Marius Moosmann, Felix Spenrath, Johannes Rosport, Philipp Melzer, Werner Kraus, Richard Bormann, Marco F. Huber:
Transfer Learning for Machine Learning-based Detection and Separation of Entanglements in Bin-Picking Applications. IROS 2022: 1123-1130 - [c70]Arik Lämmle, Philipp Tenbrock, Balázs András Bálint, Frank Nägele, Werner Kraus, József Váncza, Marco F. Huber:
Simulation-based Learning of the Peg-in-Hole Process Using Robot-Skills. IROS 2022: 9340-9346 - [c69]Christoph Hennebold, Xiaodong Mei, Ortwin Mailahn, Marco F. Huber, Oliver Mannuß:
Cooperation of Human and Active Learning based AI for Fast and Precise Complaint Management. SMC 2022: 282-287 - [i27]Raoul Schönhof, Artem Werner, Jannes Elstner, Boldizsar Zopcsak, Ramez Awad, Marco F. Huber:
Feature Visualization within an Automated Design Assessment leveraging Explainable Artificial Intelligence Methods. CoRR abs/2201.12107 (2022) - [i26]Raoul Schönhof, Jannes Elstner, Radu Manea, Steffen Tauber, Ramez Awad, Marco F. Huber:
Simplified Learning of CAD Features Leveraging a Deep Residual Autoencoder. CoRR abs/2202.10099 (2022) - [i25]Marc-André Zöller, Waldemar Titov, Thomas Schlegel, Marco F. Huber:
XAutoML: A Visual Analytics Tool for Establishing Trust in Automated Machine Learning. CoRR abs/2202.11954 (2022) - [i24]Paul-Amaury Matt, Rosina Ziegler, Danilo Brajovic, Marco Roth, Marco F. Huber:
A Nested Genetic Algorithm for Explaining Classification Data Sets with Decision Rules. CoRR abs/2209.07575 (2022) - [i23]Tobias Nagel, Marco F. Huber:
Kalman-Bucy-Informed Neural Network for System Identification. CoRR abs/2210.03424 (2022) - [i22]Simeon Brüggenjürgen, Nina Schaaf, Pascal Kerschke, Marco F. Huber:
Mixture of Decision Trees for Interpretable Machine Learning. CoRR abs/2211.14617 (2022) - 2021
- [j12]Nadia Burkart, Sebastian Robert, Marco F. Huber:
Are you sure? Prediction revision in automated decision-making. Expert Syst. J. Knowl. Eng. 38(1) (2021) - [j11]Nadia Burkart, Marco F. Huber:
A Survey on the Explainability of Supervised Machine Learning. J. Artif. Intell. Res. 70: 245-317 (2021) - [j10]Marc-André Zöller, Marco F. Huber:
Benchmark and Survey of Automated Machine Learning Frameworks. J. Artif. Intell. Res. 70: 409-472 (2021) - [j9]Christian Landgraf, Bernd Meese, Michael Pabst, Georg Martius, Marco F. Huber:
A Reinforcement Learning Approach to View Planning for Automated Inspection Tasks. Sensors 21(6): 2030 (2021) - [c68]Christian Jauch, Julia Denecke, Marco F. Huber:
Generating a Hand Pose Data Set for Vision Based Manual Assembly Assistance Systems. 3D Imaging and Applications 2021: 1-7 - [c67]Simon Dürr, Raphael Lamprecht, Matthias Kauffmann, Marco F. Huber:
Reinforcement Learning based Optimization of Bayesian Networks for Generating Feasible Vehicle Configuration Suggestions. CASE 2021: 16-22 - [c66]Christian Landgraf, Kilian Ernst, Gesine Schleth, Marc Fabritius, Marco F. Huber:
A Hybrid Neural Network Approach for Increasing the Absolute Accuracy of Industrial Robots. CASE 2021: 468-474 - [c65]Tobias Nagel, Marco F. Huber:
Autoencoder-Inspired Identification of LTI Systems. ECC 2021: 2352-2357 - [c64]Fady Aziz, Bassam Elmakhzangy, Christophe Maufroy, Urs Schneider, Marco F. Huber:
DimRad: A Radar-Based Perception System for Prosthetic Leg Barrier Traversing. EUSIPCO 2021: 1750-1754 - [c63]Kilian Kleeberger, Florian Roth, Richard Bormann, Marco F. Huber:
Automatic Grasp Pose Generation for Parallel Jaw Grippers. IAS 2021: 594-607 - [c62]Nina Schaaf, Omar de Mitri, Hang Beom Kim, Alexander Windberger, Marco F. Huber:
Towards Measuring Bias in Image Classification. ICANN (3) 2021: 433-445 - [c61]Kilian Kleeberger, Markus Völk, Richard Bormann, Marco F. Huber:
Investigations on Output Parameterizations of Neural Networks for Single Shot 6D Object Pose Estimation. ICRA 2021: 13916-13922 - [c60]Marc-André Zöller, Tien-Dung Nguyen, Marco F. Huber:
Incremental Search Space Construction for Machine Learning Pipeline Synthesis. IDA 2021: 103-115 - [c59]Raphael Lamprecht, Ferdinand Wurst, Marco F. Huber:
Reinforcement Learning based Condition-oriented Maintenance Scheduling for Flow Line Systems. INDIN 2021: 1-7 - [c58]Kilian Kleeberger, Jonathan Schnitzler, Muhammad Usman Khalid, Richard Bormann, Werner Kraus, Marco F. Huber:
Precise Object Placement with Pose Distance Estimations for Different Objects and Grippers. IROS 2021: 4639-4646 - [c57]Daniel Bargmann, Philipp Tenbrock, Lorenz Halt, Frank Nägele, Werner Kraus, Marco F. Huber:
Unobstructed Programming-by-Demonstration for Force-Based Assembly Utilizing External Force-Torque Sensors. SMC 2021: 119-124 - [i21]Kilian Kleeberger, Markus Völk, Marius Moosmann, Erik Thiessenhusen, Florian Roth, Richard Bormann, Marco F. Huber:
Transferring Experience from Simulation to the Real World for Precise Pick-And-Place Tasks in Highly Cluttered Scenes. CoRR abs/2101.04781 (2021) - [i20]Marc-André Zöller, Tien-Dung Nguyen, Marco F. Huber:
Incremental Search Space Construction for Machine Learning Pipeline Synthesis. CoRR abs/2101.10951 (2021) - [i19]Kilian Kleeberger, Markus Völk, Richard Bormann, Marco F. Huber:
Investigations on Output Parameterizations of Neural Networks for Single Shot 6D Object Pose Estimation. CoRR abs/2104.07528 (2021) - [i18]Kilian Kleeberger, Florian Roth, Richard Bormann, Marco F. Huber:
Automatic Grasp Pose Generation for Parallel Jaw Grippers. CoRR abs/2104.11660 (2021) - [i17]Fady Aziz, Bassam Elmakhzangy, Christophe Maufroy, Urs Schneider, Marco F. Huber:
DimRad: A Radar-Based Perception System for Prosthetic Leg Barrier Traversing. CoRR abs/2105.14634 (2021) - [i16]Nina Schaaf, Omar de Mitri, Hang Beom Kim, Alexander Windberger, Marco F. Huber:
Towards Measuring Bias in Image Classification. CoRR abs/2107.00360 (2021) - [i15]Raphael Lamprecht, Ferdinand Wurst, Marco F. Huber:
Reinforcement Learning based Condition-oriented Maintenance Scheduling for Flow Line Systems. CoRR abs/2108.12298 (2021) - [i14]Philipp Wagner, Xinyang Wu, Marco F. Huber:
Kalman Bayesian Neural Networks for Closed-form Online Learning. CoRR abs/2110.00944 (2021) - [i13]Kilian Kleeberger, Jonathan Schnitzler, Muhammad Usman Khalid, Richard Bormann, Werner Kraus, Marco F. Huber:
Precise Object Placement with Pose Distance Estimations for Different Objects and Grippers. CoRR abs/2110.00992 (2021) - [i12]Pascal Weller, Fady Aziz, Sherif Abdulatif, Urs Schneider, Marco F. Huber:
A MIMO Radar-based Few-Shot Learning Approach for Human-ID. CoRR abs/2110.08595 (2021) - [i11]Fady Aziz, Omar Metwally, Pascal Weller, Urs Schneider, Marco F. Huber:
A MIMO Radar-Based Metric Learning Approach for Activity Recognition. CoRR abs/2111.01939 (2021) - 2020
- [c56]Marco F. Huber:
Bayesian Perceptron: Towards fully Bayesian Neural Networks. CDC 2020: 3179-3186 - [c55]Mohamed El-Shamouty, Xinyang Wu, Shanqi Yang, Marcel Albus, Marco F. Huber:
Towards Safe Human-Robot Collaboration Using Deep Reinforcement Learning. ICRA 2020: 4899-4905 - [c54]Kilian Kleeberger, Marco F. Huber:
Single Shot 6D Object Pose Estimation. ICRA 2020: 6239-6245 - [c53]Kilian Kleeberger, Markus Völk, Marius Moosmann, Erik Thiessenhusen, Florian Roth, Richard Bormann, Marco F. Huber:
Transferring Experience from Simulation to the Real World for Precise Pick-And-Place Tasks in Highly Cluttered Scenes. IROS 2020: 9681-9688 - [c52]Nadia Burkart, Philipp M. Faller, Elisabeth Peinsipp, Marco F. Huber:
Batch-wise Regularization of Deep Neural Networks for Interpretability. MFI 2020: 216-222 - [c51]Nadia Burkart, Marco F. Huber, Mathias Anneken:
Supported Decision-Making by Explainable Predictions of Ship Trajectories. SOCO 2020: 44-54 - [i10]Kilian Kleeberger, Marco F. Huber:
Single Shot 6D Object Pose Estimation. CoRR abs/2004.12729 (2020) - [i9]Marco F. Huber:
Bayesian Perceptron: Towards fully Bayesian Neural Networks. CoRR abs/2009.01730 (2020) - [i8]Nadia Burkart, Marco F. Huber:
A Survey on the Explainability of Supervised Machine Learning. CoRR abs/2011.07876 (2020)
2010 – 2019
- 2019
- [c50]Muhammad Usman Khalid, Janik M. Hager, Werner Kraus, Marco F. Huber, Marc Toussaint:
Deep Workpiece Region Segmentation for Bin Picking. CASE 2019: 1138-1144 - [c49]Nina Schaaf, Marco F. Huber, Johannes Maucher:
Enhancing Decision Tree Based Interpretation of Deep Neural Networks through L1-Orthogonal Regularization. ICMLA 2019: 42-49 - [c48]Nadia Burkart, Marco F. Huber, Phillip Faller:
Forcing Interpretability for Deep Neural Networks through Rule-Based Regularization. ICMLA 2019: 700-705 - [c47]Patrick Dunau, Marco F. Huber, Jürgen Beyerer:
Gaussian Process based Dynamic Facial Emotion Tracking. ICPS 2019: 248-253 - [c46]Kilian Kleeberger, Christian Landgraf, Marco F. Huber:
Large-scale 6D Object Pose Estimation Dataset for Industrial Bin-Picking. IROS 2019: 2573-2578 - [c45]Nadia El Bekri, Jasmin Kling, Marco F. Huber:
A Study on Trust in Black Box Models and Post-hoc Explanations. SOCO 2019: 35-46 - [i7]Nina Schaaf, Marco F. Huber:
Enhancing Decision Tree based Interpretation of Deep Neural Networks through L1-Orthogonal Regularization. CoRR abs/1904.05394 (2019) - [i6]Marc-André Zöller, Marco F. Huber:
Survey on Automated Machine Learning. CoRR abs/1904.12054 (2019) - [i5]Muhammad Usman Khalid, Janik M. Hager, Werner Kraus, Marco F. Huber, Marc Toussaint:
Deep Workpiece Region Segmentation for Bin Picking. CoRR abs/1909.03462 (2019) - [i4]Kilian Kleeberger, Christian Landgraf, Marco F. Huber:
Large-scale 6D Object Pose Estimation Dataset for Industrial Bin-Picking. CoRR abs/1912.12125 (2019) - 2018
- [j8]Marco F. Huber, Marc-Andre Zoller, Marcus Baum:
Linear programming based time lag identification in event sequences. Autom. 98: 14-19 (2018) - [j7]Uwe D. Hanebeck, Marcus Baum, Marco F. Huber:
Guest Editorial Special Section on Multisensor Fusion and Integration for Intelligent Systems. IEEE Trans. Ind. Informatics 14(3): 1124-1126 (2018) - [c44]Patrick Dunau, Marco F. Huber, Jürgen Beyerer:
Comparison of Angle and Size Features with Deep Learning for Emotion Recognition. CIARP 2018: 602-610 - [c43]Selim Ozgen, Florian Rosenthal, Jana Mayer, Benjamin Noack, Uwe D. Hanebeck, Marco F. Huber:
Retrodiction of Data Association Probabilities via Convex Optimization. FUSION 2018: 2430-2436 - [c42]Patrick Dunau, Mike Bonny, Marco F. Huber, Jürgen Beyerer:
Reduced Feature Set for Emotion Recognition Based on Angle and Size Information. IAS 2018: 585-596 - 2017
- [j6]Marco F. Huber:
Conditional anomaly detection in event streams. Autom. 65(4): 233 (2017) - [c41]Marc-Andre Zoller, Marcus Baum, Marco F. Huber:
Framework for mining event correlations and time lags in large event sequences. INDIN 2017: 805-810 - 2016
- [c40]Marco F. Huber, Martin Voigt, Axel-Cyrille Ngonga Ngomo:
Big data architecture for the semantic analysis of complex events in manufacturing. GI-Jahrestagung 2016: 353-360 - [c39]Marco F. Huber, Andreas Merentitis, Roel Heremans, Maria E. Niessen, Christian Debes, Nikolaos Frangiadakis:
Bayesian score level fusion for facial recognition. MFI 2016: 371-378 - 2015
- [c38]Jason R. Rambach, Marco F. Huber, Mark Ryan Balthasar, Abdelhak M. Zoubir:
Collaborative multi-camera face recognition and tracking. AVSS 2015: 1-6 - [c37]Vangelis Gazis, Manuel Görtz, Marco F. Huber, Alessandro Leonardi, Kostas Mathioudakis, Alexander Wiesmaier, Florian Zeiger:
Short Paper: IoT: Challenges, projects, architectures. ICIN 2015: 145-147 - [c36]Vangelis Gazis, Manuel Görtz, Marco F. Huber, Alessandro Leonardi, Kostas Mathioudakis, Alexander Wiesmaier, Florian Zeiger, Emmanouil Vasilomanolakis:
A survey of technologies for the internet of things. IWCMC 2015: 1090-1095 - 2014
- [j5]Marco F. Huber:
Recursive Gaussian process: On-line regression and learning. Pattern Recognit. Lett. 45: 85-91 (2014) - [c35]Michael Teutsch, Thomas Mueller, Marco F. Huber, Jürgen Beyerer:
Low Resolution Person Detection with a Moving Thermal Infrared Camera by Hot Spot Classification. CVPR Workshops 2014: 209-216 - [c34]Florian Zeiger, Marco F. Huber:
Demonstration abstract: participatory sensing enabled environmental monitoring in smart cities. IPSN 2014: 337-338 - 2013
- [j4]Marco F. Huber:
Chebyshev polynomial Kalman filter. Digit. Signal Process. 23(5): 1620-1629 (2013) - [c33]Marco F. Huber, Uwe D. Hanebeck:
Gaussian filtering for polynomial systems based on moment homotopy. FUSION 2013: 1080-1087 - [c32]Marco F. Huber:
Recursive Gaussian process regression. ICASSP 2013: 3362-3366 - [c31]Alexey Pak, Marco F. Huber, Andrey Belkin:
On weak distance between distributions in application to tracking. SDF 2013: 1-6 - 2012
- [j3]Marco F. Huber:
Optimal Pruning for Multi-Step Sensor Scheduling. IEEE Trans. Autom. Control. 57(5): 1338-1343 (2012) - [j2]Marc Peter Deisenroth, Ryan D. Turner, Marco F. Huber, Uwe D. Hanebeck, Carl Edward Rasmussen:
Robust Filtering and Smoothing with Gaussian Processes. IEEE Trans. Autom. Control. 57(7): 1865-1871 (2012) - [c30]Marco F. Huber, Tobias Dencker, Masoud Roschani, Jürgen Beyerer:
Bayesian active object recognition via Gaussian process regression. FUSION 2012: 1718-1725 - [i3]Marc Peter Deisenroth, Ryan D. Turner, Marco F. Huber, Uwe D. Hanebeck, Carl Edward Rasmussen:
Robust Filtering and Smoothing with Gaussian Processes. CoRR abs/1203.4345 (2012) - [i2]Marco F. Huber:
Optimal Pruning for Multi-Step Sensor Scheduling. CoRR abs/1203.6243 (2012) - [i1]Marco F. Huber:
Adaptive Gaussian Mixture Filter Based on Statistical Linearization. CoRR abs/1203.6750 (2012) - 2011
- [c29]Marco F. Huber, Frederik Beutler, Uwe D. Hanebeck:
Semi-analytic Gaussian Assumed Density Filter. ACC 2011: 3006-3011 - [c28]Marco F. Huber:
Adaptive Gaussian mixture filter based on statistical linearization. FUSION 2011: 1-8 - [c27]Marco F. Huber, Peter Krauthausen, Uwe D. Hanebeck:
Superficial Gaussian Mixture Reduction. GI-Jahrestagung 2011: 491 - 2010
- [c26]Marco F. Huber:
On multi-step sensor scheduling via convex optimization. CIP 2010: 376-381 - [c25]Peter Krauthausen, Marco F. Huber, Uwe D. Hanebeck:
Support-vector conditional density estimation for nonlinear filtering. FUSION 2010: 1-8 - [c24]Achim Kuwertz, Marco F. Huber, Felix Sawo:
Multi-step sensor management for localizing movable sources of spatially distributed phenomena. FUSION 2010: 1-8 - [c23]Frederik Beutler, Marco F. Huber, Uwe D. Hanebeck:
Optimal stochastic linearization for range-based localization. IROS 2010: 5731-5736 - [c22]Frederik Beutler, Marco F. Huber, Uwe D. Hanebeck:
Semi-analytic stochastic linearization for range-based pose tracking. MFI 2010: 44-49
2000 – 2009
- 2009
- [b1]Marco F. Huber:
Probabilistic Framework for Sensor Management. Karlsruhe University, Germany, 2009 - [j1]Frederik Beutler, Marco F. Huber, Uwe D. Hanebeck:
Probabilistic instantaneous model-based signal processing applied to localization and tracking. Robotics Auton. Syst. 57(3): 249-258 (2009) - [c21]Uwe D. Hanebeck, Marco F. Huber, Vesa Klumpp:
Dirac mixture approximation of multivariate Gaussian densities. CDC 2009: 3851-3858 - [c20]Marco F. Huber, Achim Kuwertz, Felix Sawo, Uwe D. Hanebeck:
Distributed greedy sensor scheduling for model-based reconstruction of space-time continuous physical phenomena. FUSION 2009: 102-109 - [c19]Frederik Beutler, Marco F. Huber, Uwe D. Hanebeck:
Gaussian Filtering using state decomposition methods. FUSION 2009: 579-586 - [c18]Dennis Schieferdecker, Marco F. Huber:
Gaussian mixture reduction via clustering. FUSION 2009: 1536-1543 - [c17]Frederik Beutler, Marco F. Huber, Uwe D. Hanebeck:
Instantaneous pose estimation using rotation vectors. ICASSP 2009: 3413-3416 - [c16]Marc Peter Deisenroth, Marco F. Huber, Uwe D. Hanebeck:
Analytic moment-based Gaussian process filtering. ICML 2009: 225-232 - 2008
- [c15]Marco F. Huber, Uwe D. Hanebeck:
Progressive Gaussian mixture reduction. FUSION 2008: 1-8 - [c14]Marco F. Huber, Uwe D. Hanebeck:
Priority list sensor scheduling using optimal pruning. FUSION 2008: 1-8 - [c13]Florian Weissel, Thomas Schreiter, Marco F. Huber, Uwe D. Hanebeck:
Stochastic model predictive control of time-variant nonlinear systems with imperfect state information. MFI 2008: 40-46 - [c12]Marco F. Huber, Tim Bailey, Hugh F. Durrant-Whyte, Uwe D. Hanebeck:
On entropy approximation for Gaussian mixture random vectors. MFI 2008: 181-188 - 2007
- [c11]Florian Weissel, Marco F. Huber, Uwe D. Hanebeck:
Efficient Control of Nonlinear Noise-Corrupted Systems Using a Novel Model Predictive Control Framework. ACC 2007: 3751-3756 - [c10]Marco F. Huber, Dietrich Brunn, Uwe D. Hanebeck:
Efficient Nonlinear Measurement Updating based on Gaussian Mixture Approximation of Conditional Densities. ACC 2007: 4425-4430 - [c9]Florian Weissel, Marco F. Huber, Uwe D. Hanebeck:
A nonlinear model predictive control framework approximating noise corrupted systems with hybrid transition densities. CDC 2007: 3661-3666 - [c8]Marco F. Huber, Uwe D. Hanebeck:
The hybrid density filter for nonlinear estimation based on hybrid conditional density approximation. FUSION 2007: 1-8 - [c7]Felix Sawo, Marco F. Huber, Uwe D. Hanebeck:
Parameter identification and reconstruction for distributed phenomena based on hybrid density filter. FUSION 2007: 1-8 - [c6]Marco F. Huber, Eric Stiegeler, Uwe D. Hanebeck:
On Sensor Scheduling in Case of Unreliable Communication. GI Jahrestagung (2) 2007: 90-94 - [c5]Florian Weissel, Marco F. Huber, Uwe D. Hanebeck:
A closed-form model predictive control framework for nonlinear noise-corrupted systems. ICINCO-SPSMC 2007: 62-69 - [c4]Marco F. Huber, Uwe D. Hanebeck:
Hybrid transition density approximation for efficient recursive prediction of nonlinear dynamic systems. IPSN 2007: 283-292 - [c3]Florian Weissel, Marco F. Huber, Uwe D. Hanebeck:
Test-environment based on a team of miniature walking robots for evaluation of collaborative control methods. IROS 2007: 2474-2479 - 2006
- [c2]Marco F. Huber, Dietrich Brunn, Uwe D. Hanebeck:
Closed-Form Prediction of Nonlinear Dynamic Systems by Means of Gaussian Mixture Approximation of the Transition Density. MFI 2006: 98-103 - 2005
- [c1]Bernd Gaßmann, Marco F. Huber, Johann Marius Zöllner, Rüdiger Dillmann:
Navigation of Walking Robots: Path Planning. CLAWAR 2005: 115-122
Coauthor Index
Marc-André Zöller
aka: Marc-Andre Zoller
aka: Marc-Andre Zoller
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To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-05-28 23:11 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
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dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
