Proposing sequence genetic distances with our local greedy algorithm when genomic sampling data is unavailable. by Hannah Waddel (21520023)

Proposing sequence genetic distances with a local greedy algorithm when genomic sampling data is available for a transmission pair. by Hannah Waddel (21520023)

“…When we have available genomic sampling data, we propose genetic distances adjacent to , , and , with a binomial draw from the sample genetic distance, while respecting the current genetic distances in the source <i>i</i>.…”

Example measurement and analysis units for landscape elements. by Jaewon Han (8660295)

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Folder with all data and algorithms by Jorge Servert Lerdo de Tejada (22290001)

The iterative process of genetic algorithm in the upper-level model. by Zhipeng Huang (1759759)

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TFP results of different algorithms at different sampling intervals. by Guozhu Sui (21672798)

Algorithm testing. by Ziad M. Ali (12516532)

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Architecture of the DGAK Module and AKConv Initial Sampling Coordinate Generation Algorithm. by Siyuan Tang (5963312)

Algorithm factor level change curve. by Kuiyuan Pan (21145338)

Algorithm for optimizing the model using transformer. by Weiling Liu (1465480)

Convergence curves of the investigated algorithms. by Ziad M. Ali (12516532)

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The model parameters of SIFusion and comparative algorithms. by Song Qian (5031221)

List of the time used by each algorithm. by JiaMing Gong (20427837)

“…Additionally, we propose a density-based sampling method to improve the accuracy of classifying minority class samples into high quality samples and common samples via the density of similar samples. …”

Elements: Kingfisher: Storage Management for Data Federations (CSSI PI Meeting 2025) by Brian Bockelman (5128082)

The penetrance tables for the 8 DNME models. by Liyan Sun (760586)

“…The DNME3 100 dataset introduces a higher level of complexity with six third-order epistasis disease models, otherwise paralleling the structure of DNME 100, serving to test the algorithms’ proficiency in identifying higher-order epistasis. …”

The penetrance tables for the 8 DME models. by Liyan Sun (760586)

“…The DNME3 100 dataset introduces a higher level of complexity with six third-order epistasis disease models, otherwise paralleling the structure of DNME 100, serving to test the algorithms’ proficiency in identifying higher-order epistasis. …”

The code for sample size calculation. by Ying Zhou (25031)

“…We collected basic clinical data and multimodal ultrasound data from these patients as predictive features, with clinical pregnancy as the predictive label, for model training. …”

LSTM model’s equations. by Songsong Wang (8088293)

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The models’ training parameters. by Songsong Wang (8088293)

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Model’s measure methods. by Songsong Wang (8088293)

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