Search for Correlations Between the Results of the Density Functional Theory and Hartree–Fock Calculations Using Neural Networks and Classical Machine Learning Algorithms by Saadiallakh Normatov (20682324)

Data_Sheet_1_Cognitive Status Predicts Return to Functional Independence After Minor Stroke: A Decision Tree Analysis.docx by Mirjam R. Heldner (4476799)

“…The overall prediction accuracy to the favorable outcome was 80% in the construction cohort and reached 72% accuracy in the validation cohort. This decision tree highlighted the role of cognitive function as a crucial factor for patients to return to their usual activities after a minor stroke. …”

Discovery of Protein Modifications Using Differential Tandem Mass Spectrometry Proteomics by Paolo Cifani (1575613)

“…Termed SAMPEI for spectral alignment-based modified peptide identification, this open-source algorithm is designed for the discovery of functional protein and peptide signaling modifications, without prior knowledge of their identities. …”

Discovery of Protein Modifications Using Differential Tandem Mass Spectrometry Proteomics by Paolo Cifani (1575613)

“…Termed SAMPEI for spectral alignment-based modified peptide identification, this open-source algorithm is designed for the discovery of functional protein and peptide signaling modifications, without prior knowledge of their identities. …”

Pearson correlation coefficients between different scoring methods: manual expert scoring (MH, KG), supervised learning predictions (SVR), and decision tree clustering (DT) across... by Saeed Mohammadzadeh (13492285)

Table_1_Functional Brain Networks in Mild Cognitive Impairment Based on Resting Electroencephalography Signals.XLSX by Nadia Youssef (11586382)

“…Topological features of the functional connectivity network were analyzed using both the classical graph approach and minimum spanning tree (MST) algorithm. …”

Table_1_Functional Brain Networks in Mild Cognitive Impairment Based on Resting Electroencephalography Signals.XLSX by Nadia Youssef (11586382)

“…Topological features of the functional connectivity network were analyzed using both the classical graph approach and minimum spanning tree (MST) algorithm. …”

Design and implementation of DelaySSA. The input data for DelaySSA are reaction information, initial states, parameters and delays. Combining these into the simulation function, th... by Ziyan Jin (21021976)

Data_Sheet_1_Functional Brain Networks in Mild Cognitive Impairment Based on Resting Electroencephalography Signals.docx by Nadia Youssef (11586382)

“…Topological features of the functional connectivity network were analyzed using both the classical graph approach and minimum spanning tree (MST) algorithm. …”

Data_Sheet_1_Functional Brain Networks in Mild Cognitive Impairment Based on Resting Electroencephalography Signals.docx by Nadia Youssef (11586382)

“…Topological features of the functional connectivity network were analyzed using both the classical graph approach and minimum spanning tree (MST) algorithm. …”

Modeling with uniform <i>σ</i> values. by Giacomo Janson (8138517)

Effect of <i>|Δd</i>_<i>n</i><i>|</i> perturbation on 3D modeling. by Giacomo Janson (8138517)

Revisiting the “satisfaction of spatial restraints” approach of MODELLER for protein homology modeling by Giacomo Janson (8138517)

“…This program implements the “modeling by satisfaction of spatial restraints” strategy and its core algorithm has not been altered significantly since the early 1990s. …”

Phylogenetic tree denoting evolutionary relationship between <i>Trichuris</i> CAP proteins. by Eleanor Wainwright (14294724)

Example of use of the slightly off-axis strategies. by Raul Castañeda (13932971)

Example of the fully-compensated phase reconstruction package for off-axis DHM holograms recorded in telecentric configuration. by Raul Castañeda (13932971)

Rosenbrock function losses for . by Shikun Chen (14625352)

“…This approach bridges the gap between model accuracy and optimization efficiency, offering a practical solution for optimizing non-differentiable machine learning models that can be extended to other tree-based ensemble algorithms. The method has been successfully applied to real-world steel alloy optimization, where it achieved superior performance while maintaining all metallurgical composition constraints.…”

Rosenbrock function losses for . by Shikun Chen (14625352)

“…This approach bridges the gap between model accuracy and optimization efficiency, offering a practical solution for optimizing non-differentiable machine learning models that can be extended to other tree-based ensemble algorithms. The method has been successfully applied to real-world steel alloy optimization, where it achieved superior performance while maintaining all metallurgical composition constraints.…”

Levy function losses for . by Shikun Chen (14625352)

“…This approach bridges the gap between model accuracy and optimization efficiency, offering a practical solution for optimizing non-differentiable machine learning models that can be extended to other tree-based ensemble algorithms. The method has been successfully applied to real-world steel alloy optimization, where it achieved superior performance while maintaining all metallurgical composition constraints.…”

Rastrigin function losses for . by Shikun Chen (14625352)

“…This approach bridges the gap between model accuracy and optimization efficiency, offering a practical solution for optimizing non-differentiable machine learning models that can be extended to other tree-based ensemble algorithms. The method has been successfully applied to real-world steel alloy optimization, where it achieved superior performance while maintaining all metallurgical composition constraints.…”