| 2025 | IJCNN | On the choice of Vector Symbolic Architectures for Time Series Classification with HDC-MiniROCKET. | Marcel Unger, Kenny Schlegel, Peter Protzel, Peer Neubert |
| 2024 | IJCNN | Learnable Weighted Superposition in HDC and its Application to Multi-channel Time Series Classification. | Kenny Schlegel, Dmitri A. Rachkovskij, Evgeny Osipov, Peter Protzel, Peer Neubert |
| 2023 | IDEAL | FETCH: A Memory-Efficient Replay Approach for Continual Learning in Image Classification. | Markus Weiflog, Peter Protzel, Peer Neubert |
| 2022 | IJCNN | HDC-MiniROCKET: Explicit Time Encoding in Time Series Classification with Hyperdimensional Computing. | Kenny Schlegel, Peer Neubert, Peter Protzel |
| 2021 | ICRA | Beyond ANN: Exploiting Structural Knowledge for Efficient Place Recognition. | Stefan Schubert, Peer Neubert, Peter Protzel |
| 2021 | ICRA | SoftMP: Attentive feature pooling for joint local feature detection and description for place recognition in changing environments. | Fangming Yuan, Peer Neubert, Stefan Schubert, Peter Protzel |
| 2020 | IROS | Factor Graph based 3D Multi-Object Tracking in Point Clouds. | Johannes Pschmann, Tim Pfeifer, Peter Protzel |
| 2020 | ICRA | Unsupervised Learning Methods for Visual Place Recognition in Discretely and Continuously Changing Environments. | Stefan Schubert, Peer Neubert, Peter Protzel |
| 2019 | ICRA | Expectation-Maximization for Adaptive Mixture Models in Graph Optimization. | Tim Pfeifer, Peter Protzel |
| 2018 | IROS | Robust Sensor Fusion with Self-Tuning Mixture Models. | Tim Pfeifer, Peter Protzel |
| 2018 | KI | A Sequence-Based Neuronal Model for Mobile Robot Localization. | Peer Neubert, Subutai Ahmad, Peter Protzel |
| 2018 | KI | Towards Hypervector Representations for Learning and Planning with Schemas. | Peer Neubert, Peter Protzel |
| 2017 | IROS | Sampling-based methods for visual navigation in 3D maps by synthesizing depth images. | Peer Neubert, Stefan Schubert, Peter Protzel |
| 2016 | ETFA | Robust factor graph optimization - a comparison for sensor fusion applications. | Tim Pfeifer, Peter Weissig, Sven Lange, Peter Protzel |
| 2014 | ICPR | Compact Watershed and Preemptive SLIC: On Improving Trade-offs of Superpixel Segmentation Algorithms. | Peer Neubert, Peter Protzel |
| 2013 | BMVC | Evaluating Superpixels in Video: Metrics Beyond Figure-Ground Segmentation. | Peer Neubert, Peter Protzel |
| 2013 | ICRA | Incremental smoothing vs. filtering for sensor fusion on an indoor UAV. | Sven Lange, Niko Snderhauf, Peter Protzel |
| 2013 | ICRA | Switchable constraints vs. max-mixture models vs. RRR - A comparison of three approaches to robust pose graph SLAM. | Niko Snderhauf, Peter Protzel |
| 2012 | IROS | Switchable constraints for robust pose graph SLAM. | Niko Snderhauf, Peter Protzel |
| 2012 | ICRA | Towards a robust back-end for pose graph SLAM. | Niko Snderhauf, Peter Protzel |
| 2011 | IROS | BRIEF-Gist - Closing the loop by simple means. | Niko Snderhauf, Peter Protzel |
| 2010 | ETFA | Beyond RatSLAM: Improvements to a biologically inspired SLAM system. | Niko Snderhauf, Peter Protzel |
| 2010 | IROS | The causal update filter - A novel biologically inspired filter paradigm for appearance-based SLAM. | Niko Snderhauf, Peer Neubert, Peter Protzel |
| 2010 | KI | From Neurons to Robots: Towards Efficient Biologically Inspired Filtering and SLAM. | Niko Snderhauf, Peter Protzel |
| 2008 | ETFA | A fast visual line segment tracker. | Peer Neubert, Peter Protzel, Teresa A. Vidal-Calleja, Simon Lacroix |
| 2006 | ICRA | Bringing Robotics closer to Students - a Threefold Approach. | Niko Snderhauf, Thomas Krause, Peter Protzel |
| 2005 | ICRA | RoboKing - Bringing Robotics closer to Pupils. | Niko Snderhauf, Thomas Krause, Peter Protzel |
| 2002 | ICANN | Finding the Optimal Continuous Model for Discrete Data by Neural Network Interpolation of Fractional Iteration. | Lars Kindermann, Achim Lewandowski, Peter Protzel |
| 2001 | ICANN | Approximation of Time-Varying Functions with Local Regression Models. | Achim Lewandowski, Peter Protzel |
| 2001 | IDA | Predicting Time-Varying Functions with Local Models. | Achim Lewandowski, Peter Protzel |
| 1996 | ESANN | FlexNet - A flexible neural network construction algorithm. | Karim Mohraz, Peter Protzel |
| 1984 | GI | Leistungsmerkmale dienstintegrierender Digitalnetze. | Harro L. Hartmann, Peter Protzel, H. A. Ebbecke |