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Evaluating GAM-Like Neural Network Architectures for Interpretable Machine Learning
(2019-05)
In many machine learning applications, interpretability is of the utmost importance. Artificial intelligence is proliferating, but before you entrust your finances, your well-being, or even your life to a machine, you’d ...
MISSISSIPPIAN MERAMEC LITHOLOGIES AND PETROPHYSICAL PROPERTY VARIABILITY, STACK TREND, ANADARKO BASIN, OKLAHOMA
(2019-05)
Mississippian Meramec reservoirs of the STACK (Sooner Trend in the Anadarko [Basin] in Canadian and Kingfisher counties) play are comprised of silty limestones, calcareous siltstones, argillaceous-calcareous siltstones, ...
Predicting wine quality and/or taste through the use of a latent ODE-RNN Neural Net
(2019-12-13)
It is common for recommendation systems to use clustering techniques for finding similar products for the downstream user. These models do not always incorporate time as a variable when recommending an item. If our ...
Imbalanced Learning with Parametric Linear Programming Support Vector Machine For Weather Data Application
(2019-05-10)
Learning from imbalanced data sets is one of the aspects of predictive modeling and machine learning that has taken a lot of attention in the last decade. Multiple research projects have been carried out to adjust the ...
DATA-DRIVEN REAL-TIME GEOSTEERING USING SURFACE DRILLING DATA
(2019-12-13)
In this thesis I present a method for estimating lithology or deriving formation properties from real-time surface drilling data. This information can then be used to enhance real-time geosteering capabilities. Current ...