Dice score for various <i>α</i> values (from the Eq 8) for the tracking of the CST and for the iFOD and PTT algorithms. حسب Thomas Durantel (20933812)

Test functions. حسب Kejia Liu (5699651)

"…Its restrictions block GEP from successfully handling high-dimensional along with complex optimization problems. …"

Risk and density functions for standard relapse from remission condition to disease <i>b</i> condition (similar shapes for standard relapse to disease <i>a</i>). حسب Benoîte de Saporta (20454662)

Acc epoch loss curve of IPCA algorithm. حسب Lu Lin (201289)

<b>Gene Catalog and Associated Functional Data</b> for BioProject PRJNA1311452 حسب Satheeswaran Thangaraj (22187269)

Observed distributions of ARI ×100 from the FRECL partition after consensus clustering; against the number of runs. حسب Susana Conde (5495675)

Strong negative correlation between the precision of algorithms and the evolutionary distance from the training data. حسب Sven B. Gould (12237287)

Python code for a rule-based NLP model for mapping circular economy indicators to SDGs حسب Zahir Barahmand (18008947)

"…The package includes:</p><ul><li>The complete Python codebase implementing the classification algorithm</li><li>A detailed manual outlining model features, requirements, and usage instructions</li><li>Sample input CSV files and corresponding processed output files to demonstrate functionality</li><li>Keyword dictionaries for all 17 SDGs, distinguishing strong and weak matches</li></ul><p dir="ltr">These materials enable full reproducibility of the study, facilitate adaptation for related research, and offer transparency in the methodological framework.…"

Multimodal reference functions. حسب Ruiyu Zhan (21602031)

"…Utilizing the diabetes dataset from 130 U.S. hospitals, the LGWO-BP algorithm achieved a precision rate of 0.97, a sensitivity of 1.00, a correct classification rate of 0.99, a harmonic mean of precision and recall (F1-score) of 0.98, and an area under the ROC curve (AUC) of 1.00. …"

Flow chart diagram of blind quantum algorithm. حسب Sultan H. Almotiri (14029251)

"…Our study addresses five major components of the quantum method to overcome these challenges: lattice-based cryptography, fully homomorphic algorithms, quantum key distribution, quantum hash functions, and blind quantum algorithms. …"

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

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

Various MFOs from three mechanisms. حسب Jingjing Ma (419752)

Rosenbrock function losses for . حسب Shikun Chen (14625352)

"…The approach leverages gradient information from neural networks to guide SLSQP optimization while maintaining XGBoost’s prediction precision. …"

Rosenbrock function losses for . حسب Shikun Chen (14625352)

"…The approach leverages gradient information from neural networks to guide SLSQP optimization while maintaining XGBoost’s prediction precision. …"

Levy function losses for . حسب Shikun Chen (14625352)

"…The approach leverages gradient information from neural networks to guide SLSQP optimization while maintaining XGBoost’s prediction precision. …"

Rastrigin function losses for . حسب Shikun Chen (14625352)

"…The approach leverages gradient information from neural networks to guide SLSQP optimization while maintaining XGBoost’s prediction precision. …"

Levy function losses for . حسب Shikun Chen (14625352)

"…The approach leverages gradient information from neural networks to guide SLSQP optimization while maintaining XGBoost’s prediction precision. …"

Rastrigin function losses for . حسب Shikun Chen (14625352)

"…The approach leverages gradient information from neural networks to guide SLSQP optimization while maintaining XGBoost’s prediction precision. …"

Levy function losses for . حسب Shikun Chen (14625352)

"…The approach leverages gradient information from neural networks to guide SLSQP optimization while maintaining XGBoost’s prediction precision. …"