Introspective Robot Perception Using Smoothed Predictions from Bayesian Neural Networks. - Jianxiang Feng; Maximilian Durner; Zoltán-Csaba Márton; Ferenc Bálint-Benczédi; Rudolph Triebel (ISRR, 2019)

Estimating Model Uncertainty of Neural Networks in Sparse Information Form. - Jongseok Lee; Matthias Humt; Jianxiang Feng; Rudolph Triebel (ICML, 2020)

Trust Your Robots! Predictive Uncertainty Estimation of Neural Networks with Sparse Gaussian Processes. - Jongseok Lee; Jianxiang Feng; Matthias Humt; Marcus Gerhard Müller; Rudolph Triebel (CoRL, 2021)

An accurate and easy deployment array gain-phase error calibration method for DoA estimation in Wi-Fi network. - Zhian Deng; Jianxiang Feng; Shengao Wang; Zhiyu Qu; Jiahao Zhang; Weijian Si (Ad Hoc Networks, 2021)

Bridging the Last Mile in Sim-to-Real Robot Perception via Bayesian Active Learning. - Jianxiang Feng; Jongseok Lee; Maximilian Durner; Rudolph Triebel (CoRR, 2021)

Bayesian Active Learning for Sim-to-Real Robotic Perception. - Jianxiang Feng; Jongseok Lee; Maximilian Durner; Rudolph Triebel (IROS, 2022)

Virtual Reality via Object Poses and Active Learning: Realizing Telepresence Robots with Aerial Manipulation Capabilities. - Jongseok Lee; Ribin Balachandran; Konstantin Kondak; Andre Coelho; Marco De Stefano; Matthias Humt; Jianxiang Feng; Tamim Asfour; Rudolph Triebel (CoRR, 2022)

Topology-Matching Normalizing Flows for Out-of-Distribution Detection in Robot Learning. - Jianxiang Feng; Jongseok Lee; Simon Geisler; Stephan Günnemann; Rudolph Triebel (CoRL, 2023)

Efficient and Feasible Robotic Assembly Sequence Planning via Graph Representation Learning. - Matan Atad; Jianxiang Feng; Ismael Rodríguez; Maximilian Durner; Rudolph Triebel (IROS, 2023)

Density-based Feasibility Learning with Normalizing Flows for Introspective Robotic Assembly. - Jianxiang Feng; Matan Atad; Ismael Rodríguez; Maximilian Durner; Stephan Günnemann; Rudolph Triebel (CoRR, 2023)

Virtual Reality via Object Pose Estimation and Active Learning: Realizing Telepresence Robots with Aerial Manipulation Capabilities. - Jongseok Lee; Ribin Balachandran; Konstantin Kondak; Andre Coelho; Marco De Stefano; Matthias Humt; Jianxiang Feng; Tamim Asfour; Rudolph Triebel (Field Robotics, 2023)

Reliability analysis and optimization of multi-phased spaceflight with backup missions and mixed redundancy strategy. - Xiang-Yu Li 007; Xiaopeng Li; Jianxiang Feng; Congming Li; Xiaoyan Xiong; Hong-Zhong Huang (Reliab. Eng. Syst. Saf., 2023)

A survey of uncertainty in deep neural networks. - Jakob Gawlikowski; Cedrique Rovile Njieutcheu Tassi; Mohsin Ali; Jongseok Lee; Matthias Humt; Jianxiang Feng; Anna M. Kruspe; Rudolph Triebel; Peter Jung 001; Ribana Roscher; Muhammad Shahzad 002; Wen Yang 001; et al. (Artif. Intell. Rev., 2023)

Multi-fingered Dynamic Grasping for Unknown Objects. - Yannick Burkhardt; Qian Feng; Jianxiang Feng; Karan Sharma; Zhaopeng Chen; Alois Knoll (Humanoids, 2024)

DexGANGrasp: Dexterous Generative Adversarial Grasping Synthesis for Task-Oriented Manipulation. - Qian Feng; David S. Martinez Lema; Mohammadhossein Malmir; Hang Li; Jianxiang Feng; Zhaopeng Chen; Alois Knoll (Humanoids, 2024)

Evaluating Uncertainty-based Failure Detection for Closed-Loop LLM Planners. - Zhi Zheng; Qian Feng; Hang Li; Alois Knoll; Jianxiang Feng (CoRR, 2024)

Language-Guided Object-Centric Diffusion Policy for Collision-Aware Robotic Manipulation. - Hang Li; Qian Feng; Zhi Zheng; Jianxiang Feng; Alois Knoll (CoRR, 2024)

FFHFlow: A Flow-based Variational Approach for Multi-fingered Grasp Synthesis in Real Time. - Qian Feng; Jianxiang Feng; Zhaopeng Chen; Rudolph Triebel; Alois Knoll (CoRR, 2024)

LensDFF: Language-enhanced Sparse Feature Distillation for Efficient Few-Shot Dexterous Manipulation. - Qian Feng; David S. Martinez Lema; Jianxiang Feng; Zhaopeng Chen; Alois Knoll (CoRR, 2025)