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driven optimization » design optimization (Expand Search), guided optimization (Expand Search), dose optimization (Expand Search)
model optimization » codon optimization (Expand Search), global optimization (Expand Search), based optimization (Expand Search)
binary death » binary health (Expand Search), binary data (Expand Search), binary depot (Expand Search)
binary task » binary mask (Expand Search)
task driven » task derived (Expand Search), mapk driven (Expand Search), state driven (Expand Search)
death model » each model (Expand Search), path model (Expand Search), dea model (Expand Search)
driven optimization » design optimization (Expand Search), guided optimization (Expand Search), dose optimization (Expand Search)
model optimization » codon optimization (Expand Search), global optimization (Expand Search), based optimization (Expand Search)
binary death » binary health (Expand Search), binary data (Expand Search), binary depot (Expand Search)
binary task » binary mask (Expand Search)
task driven » task derived (Expand Search), mapk driven (Expand Search), state driven (Expand Search)
death model » each model (Expand Search), path model (Expand Search), dea model (Expand Search)
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1
Thesis-RAMIS-Figs_Slides
Published 2024“…In the context of facies recovery using simulations, the task of optimal sampling is formalized and addressed using a maximum information extraction criterion. …”
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2
Machine Learning-Ready Dataset for Cytotoxicity Prediction of Metal Oxide Nanoparticles
Published 2025“…</p><p dir="ltr">Encoding: Categorical variables such as surface coating and cell type were grouped into logical classes and label-encoded to enable model compatibility.</p><p dir="ltr"><b>Applications and Model Compatibility:</b></p><p dir="ltr">The dataset is optimized for use in supervised learning workflows and has been tested with algorithms such as:</p><p dir="ltr">Gradient Boosting Machines (GBM),</p><p dir="ltr">Support Vector Machines (SVM-RBF),</p><p dir="ltr">Random Forests, and</p><p dir="ltr">Principal Component Analysis (PCA) for feature reduction.…”