2 citations · 2 across the 6 of their papers we have counts for
10 papers
Higher-Order Hit-&-Run Samplers for Linearly Constrained Densities
Richard D. Paul, Anton Stratmann, Johann F. Jadebeck +4
Markov chain Monte Carlo (MCMC) sampling of densities restricted to linearly constrained domains is an important task arising in Bayesian treatment of inverse problems in the natur…
Physics-Guided Diffusion Priors for Multi-Slice Reconstruction in Scientific Imaging
Laurentius Valdy, Richard D. Paul, Alessio Quercia +4
Accurate multi-slice reconstruction from limited measurement data is crucial to speed up the acquisition process in medical and scientific imaging. However, it remains challenging…
acia-workflows: Automated Single-cell Imaging Analysis for Scalable and Deep Learning-based Live-cell Imaging Analysis Workflows
Johannes Seiffarth, Keitaro Kasahara, Michelle Bund +7
Live-cell imaging (LCI) technology enables the detailed spatio-temporal characterization of living cells at the single-cell level, which is critical for advancing research in the l…
Efficient Epistemic Uncertainty Estimation in Cerebrovascular Segmentation
Omini Rathore, Richard Paul, Abigail Morrison +2
Brain vessel segmentation of MR scans is a critical step in the diagnosis of cerebrovascular diseases. Due to the fine vessel structure, manual vessel segmentation is time consumin…
How To Make Your Cell Tracker Say "I dunno!"
Richard D. Paul, Johannes Seiffarth, David Rügamer +2
Cell tracking is a key computational task in live-cell microscopy, but fully automated analysis of high-throughput imaging requires reliable and, thus, uncertainty-aware data analy…
1LoRA: Summation Compression for Very Low-Rank Adaptation
Alessio Quercia, Zhuo Cao, Arya Bangun +4
Parameter-Efficient Fine-Tuning (PEFT) methods have transformed the approach to fine-tuning large models for downstream tasks by enabling the adjustment of significantly fewer para…
Tracking one-in-a-million: Large-scale benchmark for microbial single-cell tracking with experiment-aware robustness metrics
J. Seiffarth, L. Blöbaum, R. D. Paul +6
Tracking the development of living cells in live-cell time-lapses reveals crucial insights into single-cell behavior and presents tremendous potential for biomedical and biotechnol…
Parameter-efficient Bayesian Neural Networks for Uncertainty-aware Depth Estimation
Richard D. Paul, Alessio Quercia, Vincent Fortuin +2
State-of-the-art computer vision tasks, like monocular depth estimation (MDE), rely heavily on large, modern Transformer-based architectures. However, their application in safety-c…
Robust Approximate Characterization of Single-Cell Heterogeneity in Microbial Growth
Richard D. Paul, Johannes Seiffarth, Hanno Scharr +1
Live-cell microscopy allows to go beyond measuring average features of cellular populations to observe, quantify and explain biological heterogeneity. Deep Learning-based instance…
Dynamic Matching Algorithms in Practice
Monika Henzinger, Shahbaz Khan, Richard Paul +1
In recent years, significant advances have been made in the design and analysis of fully dynamic maximal matching algorithms. However, these theoretical results have received very…