Data_Sheet_1_A Bayesian Model to Analyze the Association of Rheumatoid Arthritis With Risk Factors and Their Interactions.PDF by Leon Lufkin (11276856)

Models’ performance without optimization. by Muhammad Usman Tariq (11022141)

“…To enhance the performance of these models, Bayesian optimization techniques were employed. Subsequently, the models were re-evaluated to compare their effectiveness. …”

RNN performance comparison with/out optimization. by Muhammad Usman Tariq (11022141)

“…To enhance the performance of these models, Bayesian optimization techniques were employed. Subsequently, the models were re-evaluated to compare their effectiveness. …”

A* Path-Finding Algorithm to Determine Cell Connections by Max Weng (22327159)

“…</p><p dir="ltr">Astrocytes were dissociated from E18 mouse cortical tissue, and image data were processed using a Cellpose 2.0 model to mask nuclei. Pixel paths were classified using a z-score brightness threshold of 1.21, optimized for noise reduction and accuracy. …”

XNet: A Bayesian Approach to Extracted Ion Chromatogram Clustering for Precursor Mass Spectrometry Data by Mathew Gutierrez (5844431)

“…While tandem mass spectrometry remains a primary method for identification and quantification, species-resolved precursor data provides a rich source of unexploited information. …”

The baseline case–the model in the absence of sentinel plants. by Francesca A. Lovell-Read (14378253)

Proposed method approach. by Muhammad Usman Tariq (11022141)

“…To enhance the performance of these models, Bayesian optimization techniques were employed. Subsequently, the models were re-evaluated to compare their effectiveness. …”

LSTM model performance. by Muhammad Usman Tariq (11022141)

“…To enhance the performance of these models, Bayesian optimization techniques were employed. Subsequently, the models were re-evaluated to compare their effectiveness. …”

Descriptive statistics. by Muhammad Usman Tariq (11022141)

“…To enhance the performance of these models, Bayesian optimization techniques were employed. Subsequently, the models were re-evaluated to compare their effectiveness. …”

CNN-LSTM Model performance. by Muhammad Usman Tariq (11022141)

“…To enhance the performance of these models, Bayesian optimization techniques were employed. Subsequently, the models were re-evaluated to compare their effectiveness. …”

MLP Model performance. by Muhammad Usman Tariq (11022141)

“…To enhance the performance of these models, Bayesian optimization techniques were employed. Subsequently, the models were re-evaluated to compare their effectiveness. …”

RNN Model performance. by Muhammad Usman Tariq (11022141)

“…To enhance the performance of these models, Bayesian optimization techniques were employed. Subsequently, the models were re-evaluated to compare their effectiveness. …”

CNN Model performance. by Muhammad Usman Tariq (11022141)

“…To enhance the performance of these models, Bayesian optimization techniques were employed. Subsequently, the models were re-evaluated to compare their effectiveness. …”

Bi-directional LSTM Model performance. by Muhammad Usman Tariq (11022141)

“…To enhance the performance of these models, Bayesian optimization techniques were employed. Subsequently, the models were re-evaluated to compare their effectiveness. …”

Flowchart scheme of the ML-based model. by Noshaba Qasmi (20405009)

“…<b>I)</b> Testing data consisting of 20% of the entire dataset. <b>J)</b> Optimization of hyperparameter tuning. <b>K)</b> Algorithm selection from all models. …”

Supplementary information for Efficient distributed edge computing for dependent delay-sensitive tasks in multi-operator multi-access networks by Alia Asheralieva (17562462)

“…We prove that the game has a perfect Bayesian equilibrium (PBE) yielding unique optimal values, and formulate new Bayesian reinforcement learning and Bayesian deep reinforcement learning algorithms enabling each PN to reach the PBE autonomously (without communicating with other PNs).…”

<b>Spatial modeling of gully density on the Qinghai-Tibet Plateau: Application of hyperparameter optimization in interpretable machine learning</b> by Zhoujiang Liu (22741966)

“…Various machine learning models were used, and different hyperparameter optimization algorithms were selected to train the models to obtain the best model. …”

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). …”

Data_Sheet_1_A Machine-Learning Approach for Dynamic Prediction of Sepsis-Induced Coagulopathy in Critically Ill Patients With Sepsis.docx by Qin-Yu Zhao (10014626)

Data_Sheet_2_A Machine-Learning Approach for Dynamic Prediction of Sepsis-Induced Coagulopathy in Critically Ill Patients With Sepsis.xlsx by Qin-Yu Zhao (10014626)