4 citations · 4 across the 2 of their papers we have counts for
3 papers
stat.CO2023★ 4 cited
Taming numerical imprecision by adapting the KL divergence to negative probabilities
Simon Pfahler, Peter Georg, Rudolf Schill +4
The Kullback-Leibler (KL) divergence is frequently used in data science. For discrete distributions on large state spaces, approximations of probability vectors may result in a few…
stat.ML2021
Differentiated uniformization: A new method for inferring Markov chains on combinatorial state spaces including stochastic epidemic models
Kevin Rupp, Rudolf Schill, Jonas Süskind +6
Motivation: We consider continuous-time Markov chains that describe the stochastic evolution of a dynamical system by a transition-rate matrix which depends on a parameter .…
math.NA2020
Low-rank tensor methods for Markov chains with applications to tumor progression models
Peter Georg, Lars Grasedyck, Maren Klever +3
Continuous-time Markov chains describing interacting processes exhibit a state space that grows exponentially in the number of processes. This state-space explosion renders the com…