datasheet1_Graph Neural Networks for Maximum Constraint Satisfaction.pdf حسب Jan Tönshoff (10192709)

Table_1_bSRWPSO-FKNN: A boosted PSO with fuzzy K-nearest neighbor classifier for predicting atopic dermatitis disease.docx حسب Yupeng Li (507508)

"…</p>Methods<p>This paper establishes a medical prediction model for the first time on the basis of the enhanced particle swarm optimization (SRWPSO) algorithm and the fuzzy K-nearest neighbor (FKNN), called bSRWPSO-FKNN, which is practiced on a dataset related to patients with AD. …"

Fig 1 - حسب Jakub Stoklosa (3315042)

Segmentation, trace denoising and spike extraction framework. حسب Changjia Cai (10647521)

An exemplar procedure for activity flow modeling based on the direct and shortest paths at a network density of 15%. حسب Zhengdong Wang (35299)

MCLP_quantum_annealer_V0.5 حسب Anonymous Anonymous (4854526)

"…This paper presents a quantum computing path for Transformation-to-Sampling-to-Verification of geospatial optimization problems, adaptable to the controlled qubit scale and coherence constraints under current NISQ conditions. …"

Processed dataset to train and test the WGAN-GP_IMOA_DA_Ensemble model حسب Ramya Chinnasamy (21633527)

Algoritmo de clasificación de expresiones de odio por tipos en español (Algorithm for classifying hate expressions by type in Spanish) حسب 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). …"

GSE96058 information. حسب Sepideh Zununi Vahed (9861298)

"…Subsequently, feature selection was conducted using ANOVA and binary Particle Swarm Optimization (PSO). During the analysis phase, the discriminative power of the selected features was evaluated using machine learning classification algorithms. …"

The performance of classifiers. حسب Sepideh Zununi Vahed (9861298)

"…Subsequently, feature selection was conducted using ANOVA and binary Particle Swarm Optimization (PSO). During the analysis phase, the discriminative power of the selected features was evaluated using machine learning classification algorithms. …"

Thesis-RAMIS-Figs_Slides حسب Felipe Santibañez-Leal (10967991)

"…<br><br>Finally, although the developed concepts, ideas and algorithms have been developed for inverse problems in geostatistics, the results are applicable to a wide range of disciplines where similar sampling problems need to be faced, included but not limited to design of communication networks, optimal integration and communication of swarms of robots and drones, remote sensing.…"

Flowchart of software workflow. حسب Gavrielle R. Untracht (11820311)

Image1_Applying the Hubbard-Stratonovich Transformation to Solve Scheduling Problems Under Inequality Constraints With Quantum Annealing.TIF حسب Sizhuo Yu (11429743)

"…<p>Quantum annealing is a global optimization algorithm that uses the quantum tunneling effect to speed-up the search for an optimal solution. …"

Image3_Applying the Hubbard-Stratonovich Transformation to Solve Scheduling Problems Under Inequality Constraints With Quantum Annealing.TIF حسب Sizhuo Yu (11429743)

"…<p>Quantum annealing is a global optimization algorithm that uses the quantum tunneling effect to speed-up the search for an optimal solution. …"

Image2_Applying the Hubbard-Stratonovich Transformation to Solve Scheduling Problems Under Inequality Constraints With Quantum Annealing.TIF حسب Sizhuo Yu (11429743)

"…<p>Quantum annealing is a global optimization algorithm that uses the quantum tunneling effect to speed-up the search for an optimal solution. …"

DataSheet1_Applying the Hubbard-Stratonovich Transformation to Solve Scheduling Problems Under Inequality Constraints With Quantum Annealing.pdf حسب Sizhuo Yu (11429743)

"…<p>Quantum annealing is a global optimization algorithm that uses the quantum tunneling effect to speed-up the search for an optimal solution. …"

Data_Sheet_1_Multiclass Classification Based on Combined Motor Imageries.pdf حسب Cecilia Lindig-León (7889777)

PathOlOgics_RBCs Python Scripts.zip حسب Ahmed Elsafty (16943883)

"…This process generated a ground-truth binary semantic segmentation mask and determined the bounding box coordinates (XYWH) for each cell. …"

Spontaneous ERG-based random forest model discriminates control and disease cases in rodent models of obesity and type 1 diabetes and predicts disease evolution in the type 1 diabe... حسب Ramsés Noguez Imm (6658637)

Active Learning Accelerated Discovery of Stable Iridium Oxide Polymorphs for the Oxygen Evolution Reaction حسب Raul A. Flores (2910539)

"…We emphasize that the proposed AL algorithm can be easily generalized to search for any binary metal oxide structure with a defined stoichiometry.…"