Unsupervised Machine Learning Based on Non-Negative Tensor Factorization
for Analyzing Reactive-Mixing

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Unsupervised Machine Learning Based on Non-Negative Tensor Factorization for Analyzing Reactive-Mixing

16 May 2018

Daniel O’Malley

B. S. Alexandrov

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Papers citing "Unsupervised Machine Learning Based on Non-Negative Tensor Factorization for Analyzing Reactive-Mixing"

12 / 12 papers shown

Title
Learning the Factors Controlling Mineralization for Geologic Carbon Sequestration Aleksandra Pachalieva J. Hyman Daniel O’Malley Hari S. Viswanathan G. Srinivasan 44 0 0 20 Dec 2023
GeoThermalCloud: Machine Learning for Geothermal Resource Exploration M. Mudunuru V. Vesselinov B. Ahmmed 41 3 0 17 Oct 2022
Generating Hidden Markov Models from Process Models Through Nonnegative Tensor Factorization E. Skau A. Hollis S. Eidenbenz Kim Ø. Rasmussen Boian Alexandrov 78 2 0 03 Oct 2022
$FRAPPE: $\underline{\text{F}}$ast $\underline{\text{Ra}}$nk $\underline{\text{App}}$roximation with $\underline{\text{E}}$xplainable Features for Tensors$ FRAPPE: $\underline{\text{F}}$ ast $\underline{\text{Ra}}$ nk $\underline{\text{App}}$ roximation with $\underline{\text{E}}$ xplainable Features for Tensors William Shiao Evangelos E. Papalexakis 30 3 0 19 Jun 2022
Deep Learning to Estimate Permeability using Geophysical Data M. Mudunuru E. Cromwell H. Wang X. Chen 56 13 0 08 Oct 2021
AdjointNet: Constraining machine learning models with physics-based codes S. Karra B. Ahmmed M. Mudunuru AI4CE PINN OOD 66 4 0 08 Sep 2021
A deep learning modeling framework to capture mixing patterns in reactive-transport systems N. V. Jagtap M. Mudunuru K. Nakshatrala 29 5 0 11 Jan 2021
A Comparative Study of Machine Learning Models for Predicting the State of Reactive Mixing B. Ahmmed M. Mudunuru S. Karra S. James V. Vesselinov 41 15 0 24 Feb 2020
Coarse-Grain Cluster Analysis of Tensors with Application to Climate Biome Identification Derek DeSantis P. Wolfram K. Bennett Boian Alexandrov 12 1 0 22 Jan 2020
DisCo: Physics-Based Unsupervised Discovery of Coherent Structures in Spatiotemporal Systems Adam T. Rupe Nalini Kumar V. Epifanov K. Kashinath O. Pavlyk ... M. Patwary Sergey Maidanov Victor W. Lee M. Prabhat James P. Crutchfield AI4CE 51 19 0 25 Sep 2019
Physics-Informed Machine Learning Models for Predicting the Progress of Reactive-Mixing M. Mudunuru S. Karra 45 11 0 28 Aug 2019
Using Machine Learning to Discern Eruption in Noisy Environments: A Case Study using CO2-driven Cold-Water Geyser in Chimayo, New Mexico Baichuan Yuan Yen Joe Tan M. Mudunuru O. Marcillo A. Delorey ... Jeremy D. Webster C. Gammans S. Karra G. Guthrie Paul Johnson 79 17 0 01 Oct 2018