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Found 6 papers, 2 papers with code
GeoThermalCloud: Machine Learning for Geothermal Resource Exploration
Crucial geothermal signatures often overlooked in traditional PFA are extracted using the GeoThermalCloud and analyzed by the subject matter experts to provide ML-enhanced PFA, which is informative for efficient exploration.
Learning to regularize with a variational autoencoder for hydrologic inverse analysis
A central difficulty in regularization is turning a complex conceptual model of this additional structure into a functional mathematical form to be used in the inverse analysis.
Unsupervised Phase Mapping of X-ray Diffraction Data by Nonnegative Matrix Factorization Integrated with Custom Clustering
Analyzing large X-ray diffraction (XRD) datasets is a key step in high-throughput mapping of the compositional phase diagrams of combinatorial materials libraries.
Nonnegative/binary matrix factorization with a D-Wave quantum annealer
Here, we show that the D-Wave 2X can be effectively used as part of an unsupervised machine learning method.
Identification of release sources in advection-diffusion system by machine learning combined with Green function inverse method
The identification of sources of advection-diffusion transport is based usually on solving complex ill-posed inverse models against the available state- variable data records.
Nonnegative Matrix Factorization for identification of unknown number of sources emitting delayed signals
Especially difficult is the case when the number of sources of the signals with delays is unknown and has to be determined from the data as well.
