Using low-rank tensor formats to enable computations of cancer progression models in large state spaces

Simon Pfahler¹, Peter Georg¹, Y. Linda Hu², Stefan Vocht², Rudolf Schill^2,3, Andreas Lösch², Kevin Rupp^2,3, Stefan Hansch², Maren Klever⁴, Lars Grasedyck⁴, Rainer Spang², Tilo Wettig¹

¹ Department of Physics, University of Regensburg
² Department of Informatics and Data Science, University of Regensburg
³ Department of Biosystems Science and Engineering, ETH Zürich
⁴ Institute for Geometry and Applied Mathematics, RWTH Aachen University

Correspondence: simon.pfahler@ur.de

Poster

Code availability

pRC: C++ library for efficient calculations in the Tensor Train format, open source

cMHN: C++ library to work with Mutual Hazard Networks in the Tensor Train format, soon to be open source

Funding

Simulation results

The data used to plot the KL-divergences and runtimes can be accessed here:
Runtime plot:

• non-TT
• TT - RP=16, RQ=8
• TT - RP=32, RQ=8
• TT - RP=32, RQ=16

• TT - RP=16, RQ=8
• TT - RP=32, RQ=8
• TT - RP=32, RQ=16