20 citations · 59 across the 4 of their papers we have counts for
6 papers
Tensor-train approximation of the chemical master equation and its application for parameter inference
Ion Gabriel Ion, Christian Wildner, Dimitrios Loukrezis +2
In this work, we perform Bayesian inference tasks for the chemical master equation in the tensor-train format. The tensor-train approximation has been proven to be very efficient i…
Multi-StyleGAN: Towards Image-Based Simulation of Time-Lapse Live-Cell Microscopy
Christoph Reich, Tim Prangemeier, Christian Wildner +1
Time-lapse fluorescent microscopy (TLFM) combined with predictive mathematical modelling is a powerful tool to study the inherently dynamic processes of life on the single-cell lev…
Moment-Based Variational Inference for Stochastic Differential Equations
Christian Wildner, Heinz Koeppl
Existing deterministic variational inference approaches for diffusion processes use simple proposals and target the marginal density of the posterior. We construct the variational…
Maximizing Information Gain for the Characterization of Biomolecular Circuits
Tim Prangemeier, Christian Wildner, Maleen Hanst +1
Quantitatively predictive models of biomolecular circuits are important tools for the design of synthetic biology and molecular communication circuits. The information content of t…
Multiclass Yeast Segmentation in Microstructured Environments with Deep Learning
Tim Prangemeier, Christian Wildner, André O. Françani +2
Cell segmentation is a major bottleneck in extracting quantitative single-cell information from microscopy data. The challenge is exasperated in the setting of microstructured envi…
Moment-Based Variational Inference for Markov Jump Processes
Christian Wildner, Heinz Koeppl
We propose moment-based variational inference as a flexible framework for approximate smoothing of latent Markov jump processes. The main ingredient of our approach is to partition…