Matthias Humt

According to our database, Matthias Humt authored at least 11 papers between 2020 and 2023.

Collaborative distances:

• Dijkstra number of four.
• 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

BlenderProc2: A Procedural Pipeline for Photorealistic Rendering.

Maximilian Denninger, Dominik Winkelbauer, Martin Sundermeyer, Wout Boerdijk, Markus Knauer, Klaus H. Strobl, Matthias Humt, Rudolph Triebel

J. Open Source Softw., March, 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

Shape Completion with Prediction of Uncertain Regions.

Matthias Humt, Dominik Winkelbauer, Ulrich Hillenbrand

IROS, 2023

Combining Shape Completion and Grasp Prediction for Fast and Versatile Grasping with a Multi-Fingered Hand.

Matthias Humt, Dominik Winkelbauer, Ulrich Hillenbrand, Berthold Bäuml

Proceedings of the 22nd IEEE-RAS International Conference on Humanoid Robots, 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

A Two-stage Learning Architecture that Generates High-Quality Grasps for a Multi-Fingered Hand.

Dominik Winkelbauer, Berthold Bäuml, Matthias Humt, Nils Thuerey, Rudolph Triebel

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

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

Bayesian Optimization Meets Laplace Approximation for Robotic Introspection.

Matthias Humt, Jongseok Lee, Rudolph Triebel

CoRR, 2020

Learning Multiplicative Interactions with Bayesian Neural Networks for Visual-Inertial Odometry.

Kashmira Shinde, Jongseok Lee, Matthias Humt, Aydin Sezgin, Rudolph Triebel

CoRR, 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