6 papers
Consistency of Learned Sparse Grid Quadrature Rules using NeuralODEs
Hanno Gottschalk, Emil Partow, Tobias J. Riedlinger
We prove consistency of a recently proposed scheme that evaluates expected values by composing a learned transport map with Clenshaw--Curtis sparse-grid quadrature on a tractable p…
Regularity of Solutions to Beckmann's Parametric Optimal Transport
Hanno Gottschalk, Tobias J. Riedlinger
Beckmann's problem in optimal transport minimizes the total squared flux in a continuous transport problem from a source to a target distribution. In this article, the regularity t…
Towards Reliable Detection of Empty Space: Conditional Marked Point Processes for Object Detection
Tobias J. Riedlinger, Kira Maag, Hanno Gottschalk
Deep neural networks have set the state-of-the-art in computer vision tasks such as bounding box detection and semantic segmentation. Object detectors and segmentation models assig…
Probabilistic Label Spreading: Efficient and Consistent Estimation of Soft Labels with Epistemic Uncertainty on Graphs
Jonathan Klees, Tobias Riedlinger, Peter Stehr +3
Safe artificial intelligence for perception tasks remains a major challenge, partly due to the lack of data with high-quality labels. Annotations themselves are subject to aleatori…
Learning to Detect Label Errors by Making Them: A Method for Segmentation and Object Detection Datasets
Sarina Penquitt, Tobias Riedlinger, Timo Heller +2
Recently, detection of label errors and improvement of label quality in datasets for supervised learning tasks has become an increasingly important goal in both research and indust…
Numerical and statistical analysis of NeuralODE with Runge-Kutta time integration
Emily C. Ehrhardt, Hanno Gottschalk, Tobias J. Riedlinger
NeuralODE is one example for generative machine learning based on the push forward of a simple source measure with a bijective mapping, which in the case of NeuralODE is given by t…