Jianxiang Feng

According to our database, Jianxiang Feng authored at least 13 papers between 2019 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

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, Ribana Roscher, Muhammad Shahzad, Wen Yang, Richard Bamler, Xiaoxiang Zhu

Artif. Intell. Rev., October, 2023

Reliability analysis and optimization of multi-phased spaceflight with backup missions and mixed redundancy strategy.

Xiang-Yu Li, Xiaopeng Li, Jianxiang Feng, Congming Li, Xiaoyan Xiong, Hong-Zhong Huang

Reliab. Eng. Syst. Saf., September, 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, January, 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

Efficient and Feasible Robotic Assembly Sequence Planning via Graph Representation Learning.

Matan Atad, Jianxiang Feng, Ismael Rodríguez, Maximilian Durner, Rudolph Triebel

IROS, 2023

Topology-Matching Normalizing Flows for Out-of-Distribution Detection in Robot Learning.

Jianxiang Feng, Jongseok Lee, Simon Geisler, Stephan Günnemann, Rudolph Triebel

Proceedings of the Conference on Robot Learning, 2023

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

Bayesian Active Learning for Sim-to-Real Robotic Perception.

Jianxiang Feng, Jongseok Lee, Maximilian Durner, Rudolph Triebel

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2022

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

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

Trust Your Robots! Predictive Uncertainty Estimation of Neural Networks with Sparse Gaussian Processes.

Jongseok Lee, Jianxiang Feng, Matthias Humt, Marcus Gerhard Müller, Rudolph Triebel

Proceedings of the Conference on Robot Learning, 8-11 November 2021, London, UK., 2021

2020

Estimating Model Uncertainty of Neural Networks in Sparse Information Form.

Jongseok Lee, Matthias Humt, Jianxiang Feng, Rudolph Triebel

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Introspective Robot Perception Using Smoothed Predictions from Bayesian Neural Networks.

Jianxiang Feng, Maximilian Durner, Zoltán-Csaba Márton, Ferenc Bálint-Benczédi, Rudolph Triebel

Proceedings of the Robotics Research, 2019