Table_2_NeuroRA: A Python Toolbox of Representational Analysis From Multi-Modal Neural Data.pdf by Zitong Lu (9913770)

“…Moreover, RSA is suitable for researchers to compare data from different modalities and even bridge data from different species. …”

Image_1_NeuroRA: A Python Toolbox of Representational Analysis From Multi-Modal Neural Data.pdf by Zitong Lu (9913770)

“…Moreover, RSA is suitable for researchers to compare data from different modalities and even bridge data from different species. …”

Presentation_3_NeuroRA: A Python Toolbox of Representational Analysis From Multi-Modal Neural Data.pdf by Zitong Lu (9913770)

“…Moreover, RSA is suitable for researchers to compare data from different modalities and even bridge data from different species. …”

Presentation_1_NeuroRA: A Python Toolbox of Representational Analysis From Multi-Modal Neural Data.pdf by Zitong Lu (9913770)

“…Moreover, RSA is suitable for researchers to compare data from different modalities and even bridge data from different species. …”

Table_3_NeuroRA: A Python Toolbox of Representational Analysis From Multi-Modal Neural Data.pdf by Zitong Lu (9913770)

“…Moreover, RSA is suitable for researchers to compare data from different modalities and even bridge data from different species. …”

Open Binding Pose Metadynamics: An Effective Approach for the Ranking of Protein–Ligand Binding Poses by Dominykas Lukauskis (14143149)

“…OpenBPMD is powered by the OpenMM simulation engine and uses a revised scoring function. The algorithm was validated by testing it on a wide range of targets and showing that it matches or exceeds the performance of the original BPMD. …”

Open Binding Pose Metadynamics: An Effective Approach for the Ranking of Protein–Ligand Binding Poses by Dominykas Lukauskis (14143149)

“…OpenBPMD is powered by the OpenMM simulation engine and uses a revised scoring function. The algorithm was validated by testing it on a wide range of targets and showing that it matches or exceeds the performance of the original BPMD. …”

Open Binding Pose Metadynamics: An Effective Approach for the Ranking of Protein–Ligand Binding Poses by Dominykas Lukauskis (14143149)

“…OpenBPMD is powered by the OpenMM simulation engine and uses a revised scoring function. The algorithm was validated by testing it on a wide range of targets and showing that it matches or exceeds the performance of the original BPMD. …”

Pseudocode of the BBAC_I Algorithm. by Zezhi Lin (22521663)

Execution Steps of the EOF Algorithm. by Zezhi Lin (22521663)

Improved A* algorithm flowchart. by Peiying Li (797714)

“…The study conducted algorithm validation on the TurtleBot3 mobile robot, with data sourced from experimental data from a certain college. …”

Test function information. by Chuang Zhang (2199421)

“…A levy flight strategy further improves the algorithm’s ability to jump out of local minima. In this paper, 12 benchmark test functions and 8 other newer swarm intelligence algorithms are compared in terms of convergence speed and convergence accuracy to evaluate the performance of the MSIPOA algorithm. …”

Samples from IPPs with a mixture of squared exponential intensity function (<i>p</i> = 2). by M. Hassan Tanveer (9596437)

Algorithm detection steps. by José M. Rivera-Arbeláez (12418512)

Control parameters of the SOMA algorithm. by Quoc Bao Diep (18452207)

“…To optimize this cost function, we employ the self-organizing migrating algorithm, a swarm intelligence algorithm inspired by the cooperative and competitive behaviors observed in natural organisms. …”

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

Subjects:

Image collected from bank abutment. by Xiaofeng Qu (577153)

AUC scores of anomaly detection algorithms. by GaoXiang Zhao (21499525)

“…Empirical evaluations conducted on multiple benchmark datasets demonstrate that the proposed method outperforms classical anomaly detection algorithms while surpassing conventional model averaging techniques based on minimizing standard loss functions. …”

Recall scores of anomaly detection algorithms. by GaoXiang Zhao (21499525)

“…Empirical evaluations conducted on multiple benchmark datasets demonstrate that the proposed method outperforms classical anomaly detection algorithms while surpassing conventional model averaging techniques based on minimizing standard loss functions. …”

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). …”