| A survey of uncertainty in deep neural networks J Gawlikowski, CRN Tassi, M Ali, J Lee, M Humt, J Feng, A Kruspe, ... Artificial Intelligence Review 56 (Suppl 1), 1513-1589, 2023 | 1365 | 2023 |
| Blenderproc2: A procedural pipeline for photorealistic rendering M Denninger, D Winkelbauer, M Sundermeyer, W Boerdijk, MW Knauer, ... Journal of Open Source Software 8 (82), 4901, 2023 | 106 | 2023 |
| Estimating model uncertainty of neural networks in sparse information form J Lee, M Humt, J Feng, R Triebel International Conference on Machine Learning, 5702-5713, 2020 | 65 | 2020 |
| A survey of uncertainty in deep neural networks. arXiv J Gawlikowski, CRN Tassi, M Ali, J Lee, M Humt, J Feng, A Kruspe, ... arXiv preprint arXiv:2107.03342, 2021 | 30 | 2021 |
| Trust your robots! predictive uncertainty estimation of neural networks with sparse gaussian processes J Lee, J Feng, M Humt, MG Müller, R Triebel Conference on Robot Learning, 1168-1179, 2022 | 29 | 2022 |
| A survey of uncertainty in deep neural networks. arXiv 2021 J Gawlikowski, CRN Tassi, M Ali, J Lee, M Humt, J Feng, A Kruspe, ... arXiv preprint arXiv:2107.03342, 2022 | 26 | 2022 |
| Bayesian optimization meets laplace approximation for robotic introspection M Humt, J Lee, R Triebel arXiv preprint arXiv:2010.16141, 2020 | 17 | 2020 |
| Learning multiplicative interactions with Bayesian neural networks for visual-inertial odometry K Shinde, J Lee, M Humt, A Sezgin, R Triebel arXiv preprint arXiv:2007.07630, 2020 | 14 | 2020 |
| A two-stage learning architecture that generates high-quality grasps for a multi-fingered hand D Winkelbauer, B Bäuml, M Humt, N Thuerey, R Triebel 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2022 | 11 | 2022 |
| Virtual reality via object pose estimation and active learning: Realizing telepresence robots with aerial manipulation capabilities J Lee, R Balachandran, K Kondak, A Coelho, M De Stefano, M Humt, ... arXiv preprint arXiv:2210.09678, 2022 | 9 | 2022 |
| Interactive and incremental learning of spatial object relations from human demonstrations R Kartmann, T Asfour Frontiers in Robotics and AI 10, 1151303, 2023 | 6* | 2023 |
| Combining shape completion and grasp prediction for fast and versatile grasping with a multi-fingered hand M Humt, D Winkelbauer, U Hillenbrand, B Bäuml 2023 IEEE-RAS 22nd International Conference on Humanoid Robots (Humanoids), 1-8, 2023 | 4 | 2023 |
| A Survey of Uncertainty in Deep Neural Networks (Jan 2022) J Gawlikowski, CRN Tassi, M Ali, J Lee, M Humt, J Feng, A Kruspe, ... arXiv preprint arXiv:2107.03342, 0 | 4 | |
| Laplace approximation for uncertainty estimation of deep neural networks M Humt TUM, 2019 | 3 | 2019 |
| Unknown object grasping for assistive robotics E Miller, M Durner, M Humt, G Quere, W Boerdijk, AM Sundaram, F Stulp, ... 2024 IEEE International Conference on Robotics and Automation (ICRA), 18157 …, 2024 | 2 | 2024 |
| Shape completion with prediction of uncertain regions M Humt, D Winkelbauer, U Hillenbrand 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2023 | 2 | 2023 |
| Introspective Perception for Long-term Aerial Telemanipulation with Virtual Reality J Lee, R Balachandran, K Kondak, A Coelho, M De Stefano, M Humt, ... IEEE Transactions on Field Robotics, 2024 | | 2024 |
| Intelligent Dextrous Manipulation: Humanoid Agile Justin Meets Learning AI J Tenhumberg, L Sievers, D Winkelbauer, L Röstel, J Pitz, M Humt, ... 2024 IEEE International Conference on Robotics and Automation, ICRA 2024, 2024 | | 2024 |
| DLR-IB-RM-OP-2019-108 M Humt | | |
| Supplementary Materials for the Submission: Trust Your Robots! Predictive Uncertainty Estimation of Neural Networks with Sparse Gaussian Processes J Lee, J Feng, M Humt, MG Müller, R Triebel | | |
Rudolph TriebelGerman Aerospace Center (DLR) and Karlsruhe Institute of Technology (KIT)Overená e-mailová adresa na: kit.edu
