Combining learned and analytical models for predicting action effects from sensory data A Kloss, S Schaal, J Bohg The International Journal of Robotics Research, 2020 | 109* | 2020 |
How to Train Your Differentiable Filter A Kloss, G Martius, J Bohg Autonoumous Robots, 2021 | 48 | 2021 |
Differentiable factor graph optimization for learning smoothers B Yi, MA Lee, A Kloss, R Martín-Martín, J Bohg 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2021 | 28* | 2021 |
Accurate Vision-based Manipulation through Contact Reasoning A Kloss, M Bauza, J Wu, JB Tenenbaum, A Rodriguez, J Bohg 2020 IEEE International Conference on Robotics and Automation (ICRA), 6738-6744, 2020 | 22 | 2020 |
Object Detection Using Deep Learning-Learning where to search using visual attention A Kloss Universität Tübingen Tübingen, Germany, 2015 | 8 | 2015 |
Loop closure detection using depth images SA Scherer, A Kloss, A Zell 2013 European Conference on Mobile Robots, 100-106, 2013 | 8 | 2013 |
Conclusions from an object-delivery robotic competition: Sick robot day 2014 S Buck, R Hanten, G Huskić, G Rauscher, A Kloss, J Leininger, E Ruff, ... 2015 International Conference on Advanced Robotics (ICAR), 137-143, 2015 | 5 | 2015 |
Learning where to search using visual attention A Kloss, D Kappler, HPA Lensch, MV Butz, S Schaal, J Bohg 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2016 | 3 | 2016 |
Combining Analytical and Learned Models for Model Predictive Control T Baumeister, A Kloss, J Bohg NIPS Workshop, 2018 | 2 | 2018 |
On Learning Heteroscedastic Noise Models within Differentiable Bayes Filters A Kloss, J Bohg | 1 | 2018 |
Combining Learning and Structure for Robotic Manipulation A Kloss Universität Tübingen, 2021 | | 2021 |