510 citations · 1k across the 11 of their papers we have counts for
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Bayesian Optimization Meets Laplace Approximation for Robotic Introspection
Matthias Humt, Jongseok Lee, Rudolph Triebel
In robotics, deep learning (DL) methods are used more and more widely, but their general inability to provide reliable confidence estimates will ultimately lead to fragile and unre…
Learning Multiplicative Interactions with Bayesian Neural Networks for Visual-Inertial Odometry
Kashmira Shinde, Jongseok Lee, Matthias Humt +2
This paper presents an end-to-end multi-modal learning approach for monocular Visual-Inertial Odometry (VIO), which is specifically designed to exploit sensor complementarity in th…
Estimating Model Uncertainty of Neural Networks in Sparse Information Form
Jongseok Lee, Matthias Humt, Jianxiang Feng +1
We present a sparse representation of model uncertainty for Deep Neural Networks (DNNs) where the parameter posterior is approximated with an inverse formulation of the Multivariat…
Visual-Inertial Telepresence for Aerial Manipulation
Jongseok Lee, Ribin Balachandran, Yuri S. Sarkisov +6
This paper presents a novel telepresence system for enhancing aerial manipulation capabilities. It involves not only a haptic device, but also a virtual reality that provides a 3D…