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Low-rank tensor methods for Markov chains with applications to tumor progression models

Georg, Peter ; Grasedyck, Lars ; Klever, Maren ; Schill, Rudolf ; Spang, Rainer ; Wettig, Tilo
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Abstract

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 computation or storage of the time-marginal distribution, which is defined as the solution of a certain linear system, infeasible using classical methods. We consider Markov chains whose transition rates are separable ...

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