Unsupervised machine learning based on non-negative tensor factorization for analyzing reactive-mixing

Velimir V. Vesselinov, Maruti Kumar Mudunuru, Satish Karra, Dan O'Malley, Boian S. Alexandrov

Abstract: Highlights•NTFk provides an elegant way to extract hidden features in irreversible fast bimolecular reaction-diffusion systems.•Features extracted using NTFk are non-negative which is an important constraint to ensure physically meaningful decomposition of the reactive-mixing process.•Added benefit of our method is data compression along with minimal loss of information.