Linear kernel: Power and Type I error for cluster evaluation metric simulations. by Alexandria M. Jensen (6494957)

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Examples of between- and within-community Beta distributions. by Alexandria M. Jensen (6494957)

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P-values from analysis of ABIDE dataset for binary outcome of diagnostic group. by Alexandria M. Jensen (6494957)

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Examples of four simulated networks and adjacency matrices. by Alexandria M. Jensen (6494957)

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P-values from analysis of ABIDE dataset for continuous outcome of VIQ. by Alexandria M. Jensen (6494957)

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Data_Sheet_1_Metric Learning in Freewill EEG Pre-Movement and Movement Intention Classification for Brain Machine Interfaces.PDF by William Plucknett (12984758)

“…This visualizes the contribution of features that can be related to brain function.</p>…”

The Blood–Brain Barrier (BBB) Score by Mayuri Gupta (1886839)

“…An algorithm, designated “BBB Score”, composed of stepwise and polynomial piecewise functions, is herein proposed for predicting BBB penetration based on five physicochemical descriptors: number of aromatic rings, heavy atoms, MWHBN (a descriptor comprising molecular weight, hydrogen bond donor, and hydrogen bond acceptors), topological polar surface area, and pKa. …”

The Blood–Brain Barrier (BBB) Score by Mayuri Gupta (1886839)

“…An algorithm, designated “BBB Score”, composed of stepwise and polynomial piecewise functions, is herein proposed for predicting BBB penetration based on five physicochemical descriptors: number of aromatic rings, heavy atoms, MWHBN (a descriptor comprising molecular weight, hydrogen bond donor, and hydrogen bond acceptors), topological polar surface area, and pKa. …”

The Blood–Brain Barrier (BBB) Score by Mayuri Gupta (1886839)

“…An algorithm, designated “BBB Score”, composed of stepwise and polynomial piecewise functions, is herein proposed for predicting BBB penetration based on five physicochemical descriptors: number of aromatic rings, heavy atoms, MWHBN (a descriptor comprising molecular weight, hydrogen bond donor, and hydrogen bond acceptors), topological polar surface area, and pKa. …”

The PS-VAE enables a detailed brain region-to-behavior mapping in the two-view mouse dataset. by Matthew R. Whiteway (11467528)

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Code snippets to add user-specific custom functionality in PyNoetic. by Gursimran Singh (575288)

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Feature selection algorithm. by Mahmoud Zeydabadinezhad (12289570)

“…Our analysis pipeline included pre-processing steps, feature extraction from both time and frequency domains, a voting algorithm for selecting features, and model training and validation. …”

Python implementation from Symplectic decomposition from submatrix determinants by Jason L. Pereira (11598632)

“…Python implementation of the algorithm and demonstration of how to use the functions.…”

Mathematical expressions, weight functions, domains, and orthogonality conditions of various orthogonal polynomials. by Abeer Aljohani (18497914)

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Algoritmo de clasificación de expresiones de odio por tipos en español (Algorithm for classifying hate expressions by type in Spanish) by Daniel Pérez Palau (11097348)

“…</li></ul><p dir="ltr"><b>File Structure</b></p><p dir="ltr">The code generates and saves:</p><ul><li>Weights of the trained model (.h5)</li><li>Configured tokenizer</li><li>Training history in CSV</li><li>Requirements file</li></ul><p dir="ltr"><b>Important Notes</b></p><ul><li>The model excludes category 2 during training</li><li>Implements transfer learning from a pre-trained model for binary hate detection</li><li>Includes early stopping callbacks to prevent overfitting</li><li>Uses class weighting to handle category imbalances</li></ul><p dir="ltr">The process of creating this algorithm is explained in the technical report located at: Blanco-Valencia, X., De Gregorio-Vicente, O., Ruiz Iniesta, A., & Said-Hung, E. (2025). …”

Algorithm process of BPNN. by Xiaoxiang Cao (12644851)

Data_Sheet_1_Multivariate Brain Functional Connectivity Through Regularized Estimators.DOCX by Raymond Salvador (813880)

“…On the one hand, simple linear functions of all brain nodes were fitted with ridge regression. …”

Data_Sheet_2_Multivariate Brain Functional Connectivity Through Regularized Estimators.DOCX by Raymond Salvador (813880)

“…On the one hand, simple linear functions of all brain nodes were fitted with ridge regression. …”

Data_Sheet_3_Multivariate Brain Functional Connectivity Through Regularized Estimators.DOCX by Raymond Salvador (813880)

“…On the one hand, simple linear functions of all brain nodes were fitted with ridge regression. …”

Consistency of model-derived predictive patterns as a function of sample diversity. by Oualid Benkarim (9707986)