39 citations · 157 across the 21 of their papers we have counts for
29 papers
Variance Reduction in Stochastic Reaction Networks using Control Variates
Michael Backenköhler, Luca Bortolussi, Verena Wolf
Monte Carlo estimation in plays a crucial role in stochastic reaction networks. However, reducing the statistical uncertainty of the corresponding estimators requires sampling a la…
GINA: Neural Relational Inference From Independent Snapshots
Gerrit Großmann, Julian Zimmerlin, Michael Backenköhler +1
Dynamical systems in which local interactions among agents give rise to complex emerging phenomena are ubiquitous in nature and society. This work explores the problem of inferring…
Abstraction-Guided Truncations for Stationary Distributions of Markov Population Models
Michael Backenköhler, Luca Bortolussi, Gerrit Großmann +1
To understand the long-run behavior of Markov population models, the computation of the stationary distribution is often a crucial part. We propose a truncation-based approximation…
Analysis of Markov Jump Processes under Terminal Constraints
Michael Backenköhler, Luca Bortolussi, Gerrit Großmann +1
Many probabilistic inference problems such as stochastic filtering or the computation of rare event probabilities require model analysis under initial and terminal constraints. We…
Tracking the Race Between Deep Reinforcement Learning and Imitation Learning -- Extended Version
Timo P. Gros, Daniel Höller, Jörg Hoffmann +1
Learning-based approaches for solving large sequential decision making problems have become popular in recent years. The resulting agents perform differently and their characterist…
Generalized Method of Moments Estimation for Stochastic Models of DNA Methylation Patterns
Alexander Lück, Verena Wolf
With recent advances in sequencing technologies, large amounts of epigenomic data have become available and computational methods are contributing significantly to the progress of…