54 citations · 225 across the 24 of their papers we have counts for
4 papers · 1 filter
Functional Data Analysis: An Introduction and Recent Developments
Jan Gertheiss, David Rügamer, Bernard X. W. Liew +1
Functional data analysis (FDA) is a statistical framework that allows for the analysis of curves, images, or functions on higher dimensional domains. The goals of FDA, such as desc…
Towards Efficient MCMC Sampling in Bayesian Neural Networks by Exploiting Symmetry
Jonas Gregor Wiese, Lisa Wimmer, Theodore Papamarkou +3
Bayesian inference in deep neural networks is challenging due to the high-dimensional, strongly multi-modal parameter posterior density landscape. Markov chain Monte Carlo approach…
Fusing Structure from Motion and Simulation-Augmented Pose Regression from Optical Flow for Challenging Indoor Environments
Felix Ott, Lucas Heublein, David Rügamer +2
The localization of objects is a crucial task in various applications such as robotics, virtual and augmented reality, and the transportation of goods in warehouses. Recent advance…
Representation Learning for Tablet and Paper Domain Adaptation in Favor of Online Handwriting Recognition
Felix Ott, David Rügamer, Lucas Heublein +2
The performance of a machine learning model degrades when it is applied to data from a similar but different domain than the data it has initially been trained on. The goal of doma…