The run time for each algorithm in seconds. by Edward Antonian (21453161)

“…The goal of this paper is to examine several extensions to KGR/GPoG, with the aim of generalising them a wider variety of data scenarios. The first extension we consider is the case of graph signals that have only been partially recorded, meaning a subset of their elements is missing at observation time. …”

FIS image analysis using the semi-automatic algorithm. by Anna Demchenko (18449439)

Summary of the metrics of the different trained algorithms that performed best in the Testing process for each dataset. by Jaime B. Matas-Bustos (21772430)

Summary of the metrics of the different trained algorithms based on mean and 95% confidence intervals (calculated using t-Student) for the Testing process in each dataset. by Jaime B. Matas-Bustos (21772430)

Summary of the metrics of the different trained models foreach algorithm in each split for each dataset. by Jaime B. Matas-Bustos (21772430)

Schematic representation of semi-automated algorithm for organoids analyzing. by Anna Demchenko (18449439)

Kidney Transplant Biopsy-derived signature matrix of 18 cell phenotypes (KTB18) for deconvolution using the CIBERSORTx algorithm by Alexis Varin (20591600)

“…<p dir="ltr"><a href="https://www.nature.com/articles/s41587-019-0114-2" rel="noreferrer" target="_blank">CIBERSORTx</a> is an algorithm, accessible through a <a href="https://cibersortx.stanford.edu/index.php" rel="noreferrer" target="_blank">web portal</a>, designed to infer the cellular composition of bulk RNA-seq or microarray data, referred to as "mixture files". …”

Algorithm process. by Wei Cui (92129)

The Search process of the genetic algorithm. by Wenguang Li (6528113)

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The construction process of the FCM clustering algorithm. by Xini Fang (20861990)

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Effects of Nash equilibrium speed changes with the non-sensory motor algorithm on encounters, agent numbers, and payoffs. by Hiroyuki Ichijo (13891153)

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Effects of Nash equilibrium attack and defense behaviors with the sensory–motor algorithm on encounters, agent numbers, and payoffs. by Hiroyuki Ichijo (13891153)

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Credit Card Fraud Classification Using Applied Machine Learning – A Comparative Study of 24 ML Algorithms by Kelechi Amamba (21022064)

“…<p dir="ltr">Credit Card Fraud Classification Using Applied Machine Learning – A Comparative Study of 24 ML Algorithms</p><p dir="ltr">This study describes an empirical evaluation of 24 machine learning models, including Logistic Regression, Decision Trees, Random Forests, Support Vector Machines and Neural Networks using a highly imbalanced fraud dataset that reflects the real-world where the data was culled from. …”

Processed results from ECG data with the P-T algorithm. by Daehyun Kwon (11985629)

Multi-sensor fusion process and algorithm workflow. by Hongliang Zou (20707270)

Summary of the results (optimal parameters and resulting correlation coefficients) of the intersubject models for the different selections of training and test sets for Happiness/J... by Isabel Barradas (20614853)

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Automatic Prediction of Molecular Properties Using Substructure Vector Embeddings within a Feature Selection Workflow by Son Gyo Jung (17913002)

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Partial derivatives of the log-LF. by Qin Gong (118801)

“…Finally, we demonstrate effectiveness of our estimation method in practical applications using a set of real data.</p></div>…”

A. mCI curves derived from 30 days of CGM data across all individuals. by Jamison H. Burks (21029607)

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Data after data processing. by Jiaqi Wang (369548)