8 citations · 9 across the 5 of their papers we have counts for
5 papers
Can Tabular Foundation Models Guide Exploration in Robot Policy Learning?
Buqing Ou, Frederike Dümbgen
Policy optimization in high-dimensional continuous control for robotics remains a challenging problem. Predominant methods are inherently local and often require extensive tuning a…
Global Sampling-Based Trajectory Optimization for Contact-Rich Manipulation via KernelSOS
Zhongqi Wei, Frederike Dümbgen
Contact-rich manipulation is challenging due to its high dimensionality, the requirement for long time horizons, and the presence of hybrid contact dynamics. Sampling-based methods…
Realizability of Planar Point Embeddings from Angle Measurements
Frederike Dümbgen, Majed El Helou, Adam Scholefield
Localization of a set of nodes is an important and a thoroughly researched problem in robotics and sensor networks. This paper is concerned with the theory of localization from inn…
AL2: Progressive Activation Loss for Learning General Representations in Classification Neural Networks
Majed El Helou, Frederike Dümbgen, Sabine Süsstrunk
The large capacity of neural networks enables them to learn complex functions. To avoid overfitting, networks however require a lot of training data that can be expensive and time-…
Fourier-Domain Optimization for Image Processing
Majed El Helou, Frederike Dümbgen, Radhakrishna Achanta +1
Image optimization problems encompass many applications such as spectral fusion, deblurring, deconvolution, dehazing, matting, reflection removal and image interpolation, among oth…