Algorithmic experimental parameter design. by Chuanxi Xing (20141665)

“…Finally, we derive an off-grid sparse model for the reconstructed signal by exploiting sparsity in the null domain and use Bayesian learning to compute the maximum a posteriori probability of the source signal, thus achieving DOA estimation. …”

Spatial spectrum estimation for three algorithms. by Chuanxi Xing (20141665)

“…Finally, we derive an off-grid sparse model for the reconstructed signal by exploiting sparsity in the null domain and use Bayesian learning to compute the maximum a posteriori probability of the source signal, thus achieving DOA estimation. …”

ML algorithms in cyber security. by Abdullah Asım Yılmaz (20715311)

Flowchart of the subspace fitting algorithm for interpolated coprime arrays. by Chuanxi Xing (20141665)

Risk element category diagram. by Yao Hu (3479972)

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

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Mitochondrial toxic prediction of marine alga toxins using a predictive model based on feature coupling and ensemble learning algorithms by Guangyin Jia (21075537)

“…By comparing 8 machine learning algorithms and using a weighted soft voting method to integrate the two optimal algorithms, we established 108 prediction models and identified the best ensemble learning model MACCS_LK for screening and defining its application domain. …”

Performance of machine learning algorithms. by Wenxue Liu (6877754)

Table 6_Predictive prioritization of genes significantly associated with biotic and abiotic stresses in maize using machine learning algorithms.xlsx by Anjan Kumar Pradhan (9386369)

“…These genes had an abundance of antioxidant responsive elements and abscisic acid responsive elements in their promoter region, suggesting their role in stress response. …”

Table 7_Predictive prioritization of genes significantly associated with biotic and abiotic stresses in maize using machine learning algorithms.xlsx by Anjan Kumar Pradhan (9386369)

“…These genes had an abundance of antioxidant responsive elements and abscisic acid responsive elements in their promoter region, suggesting their role in stress response. …”

Table 3_Predictive prioritization of genes significantly associated with biotic and abiotic stresses in maize using machine learning algorithms.xlsx by Anjan Kumar Pradhan (9386369)

“…These genes had an abundance of antioxidant responsive elements and abscisic acid responsive elements in their promoter region, suggesting their role in stress response. …”

Table 2_Predictive prioritization of genes significantly associated with biotic and abiotic stresses in maize using machine learning algorithms.xlsx by Anjan Kumar Pradhan (9386369)

“…These genes had an abundance of antioxidant responsive elements and abscisic acid responsive elements in their promoter region, suggesting their role in stress response. …”

Table 1_Predictive prioritization of genes significantly associated with biotic and abiotic stresses in maize using machine learning algorithms.xlsx by Anjan Kumar Pradhan (9386369)

“…These genes had an abundance of antioxidant responsive elements and abscisic acid responsive elements in their promoter region, suggesting their role in stress response. …”

Table 4_Predictive prioritization of genes significantly associated with biotic and abiotic stresses in maize using machine learning algorithms.xlsx by Anjan Kumar Pradhan (9386369)

“…These genes had an abundance of antioxidant responsive elements and abscisic acid responsive elements in their promoter region, suggesting their role in stress response. …”

Table 5_Predictive prioritization of genes significantly associated with biotic and abiotic stresses in maize using machine learning algorithms.xlsx by Anjan Kumar Pradhan (9386369)

“…These genes had an abundance of antioxidant responsive elements and abscisic acid responsive elements in their promoter region, suggesting their role in stress response. …”

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

“…<p>Algorithm for optimizing the model using transformer.…”

Algorithm used for the determination of the model parametric values. by Jonathan Côté (527819)

“…<p>Algorithm used for the determination of the model parametric values.…”