| 2025 | ICRA | Language-Guided Object-Centric Diffusion Policy for Generalizable and Collision-Aware Manipulation. | Hang Li, Qian Feng, Zhi Zheng, Jianxiang Feng, Zhaopeng Chen, Alois Knoll |
| 2025 | IROS | LensDFF: Language-enhanced Sparse Feature Distillation for Efficient Few-Shot Dexterous Manipulation. | Qian Feng, Alois Knoll, David S. Martinez Lema, Zhaopeng Chen, Jianxiang Feng |
| 2023 | CoRL | Topology-Matching Normalizing Flows for Out-of-Distribution Detection in Robot Learning. | Jianxiang Feng, Jongseok Lee, Simon Geisler, Stephan Gnnemann, Rudolph Triebel |
| 2023 | IROS | Efficient and Feasible Robotic Assembly Sequence Planning via Graph Representation Learning. | Matan Atad, Jianxiang Feng, Ismael Rodrguez, Maximilian Durner, Rudolph Triebel |
| 2022 | IROS | Bayesian Active Learning for Sim-to-Real Robotic Perception. | Jianxiang Feng, Jongseok Lee, Maximilian Durner, Rudolph Triebel |
| 2021 | CoRL | Trust Your Robots! Predictive Uncertainty Estimation of Neural Networks with Sparse Gaussian Processes. | Jongseok Lee, Jianxiang Feng, Matthias Humt, Marcus Gerhard Mller, Rudolph Triebel |
| 2020 | ICML | Estimating Model Uncertainty of Neural Networks in Sparse Information Form. | Jongseok Lee, Matthias Humt, Jianxiang Feng, Rudolph Triebel |
| 2019 | ISRR | Introspective Robot Perception Using Smoothed Predictions from Bayesian Neural Networks. | Jianxiang Feng, Maximilian Durner, Zoltn-Csaba Mrton, Ferenc Blint-Benczdi, Rudolph Triebel |