A Deep-Learned Monolithic Nanoparticle Asymmetric Thermal Flow Sensor for Flow Vector Estimation by Huijae Park (18509359)

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A Deep-Learned Monolithic Nanoparticle Asymmetric Thermal Flow Sensor for Flow Vector Estimation by Huijae Park (18509359)

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Ablation studies of the CNN-BiGRU model optimized via the GWO algorithm across LendingClub Loan Data and German Credit Data. The evaluation metrics include MAE, MAPE, RMSE, and MSE... by Yetong Fang (21433414)

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Sequence patterns of Ig-domain variants in WebLogo format. by Caesar Tawfeeq (21087272)

Biomass data and prediction model of rice heading stage in Haitang district, Sanya City, Hainan Province. by Wanyi He (14164810)

“…</p><p dir="ltr">2. "Data Set" folder: contains all data extracted from UAV images of sampling points, raw biomass modeling data and normalized biomass modeling data, providing rich data resources for subsequent research.…”

Structure of a modern antivirus solution by Paul A. Gagniuc (1818325)

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Summary of data collection schedule during phase 1. by Hye Jun Lee (9220861)

Machine Learning Models for Efficient Property Prediction of ABX₃ Materials: A High-Throughput Approach by Soundous Touati (20282599)

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Machine Learning Models for Efficient Property Prediction of ABX₃ Materials: A High-Throughput Approach by Soundous Touati (20282599)

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Machine Learning Models for Efficient Property Prediction of ABX₃ Materials: A High-Throughput Approach by Soundous Touati (20282599)

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6 data sets included in this study. by Xihao Shen (20347942)

Comparing AUROC across several deep learning techniques for the classification of sepsis on complete blood count data (higher values represent better performance). We evaluated the... by Daniel Walke (21680915)

Data Sheet 1_Machine-learning detection of stress severity expressed on a continuous scale using acoustic, verbal, visual, and physiological data: lessons learned.pdf by Marketa Ciharova (8991782)

“…Stress monitoring may be supported by valid and reliable machine-learning algorithms. However, investigation of algorithms detecting stress severity on a continuous scale is missing due to high demands on data quality for such analyses. …”

Supplementary file 1_Integrating GWAS and machine learning for disease risk prediction in the Taiwanese Hakka population.docx by Jing-Hong Xiao (22780781)

“…After standard quality control, 295,589 SNPs were retained. Fourteen machine-learning algorithms were evaluated using SNPs selected through traditional GWAS filtering and refined via wrapper-based feature selection with a best-first search algorithm. …”

Blessing from Human-AI Interaction: Super Policy Learning in Confounded Environments by Jiayi Wang (294312)

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Improving Machine Learning Classification Predictions through SHAP and Features Analysis Interpretation by Leonardo Bernal (22461790)

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F1 results (%) compared among methods, the LACK algorithm cannot work on the GRAZ02 dataset and is replaced with “—”. The best results are highlighted in bold. by Hui Yang (91136)

Data sets implemented for analysis. by Nan Huang (464390)

The results of Federated Harmony on large scale dataset. by Ruizhi Yuan (16864629)

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The Workflow of Federated Harmony. by Ruizhi Yuan (16864629)

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