Multi-scale detection of hierarchical community architecture in structural and functional brain networks by Arian Ashourvan (6685232)

“…<div><p>Community detection algorithms have been widely used to study the organization of complex networks like the brain. …”

Local topological scales of hierarchical community organization in structural and functional brain graphs. by Arian Ashourvan (6685232)

The effect of different loss functions on our model. by Yiyang Shi (16929122)

Loss function and accuracy during training. by Shuang Guo (294074)

GA and loss function (Loss_L) parameters are optimized using their search spaces through the hyperparameter tuning. by Burcu Ozek (16949357)

Algorithm performance compared to mean of expert manual counts with varying axial sampling. by Adam L. Tyson (10892822)

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Confusion matrix diagram of the original and improved algorithms. by Jia Li (160557)

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QLIKE loss function results for ANN and SVM models. by Shusheng Ding (11663294)

The optimal solution set of NYN by using different algorithms. by Yi Tao (178829)

Subjects: “…evolutionary genetic algorithm…”

The optimal solution set of HN by using different algorithms. by Yi Tao (178829)

Subjects: “…evolutionary genetic algorithm…”

Precision metric results and curves and loss values for 40 epoch rounds and loss function transformation curves. by Xia Zhao (215170)

FAR-1: A Fast Integer Reduction Algorithm Compared to Collatz and Half-Collatz by Faizan Ali (21689861)

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Prediction of oncogenes (OG), tumor suppressors (TS) and loss of function (LOF) mutations. by Oveis Jamialahmadi (6619289)

Effects of activation function on training accuracy and training loss. by Xinwu Du (14626908)

Performance comparison of different IoU loss functions. by Wenhao Ren (2561731)

Comparison of packet loss quantity. by Jianpeng Zhang (528185)

Sub-network model structure in the LMPEC algorithm. by Hao Wu (65943)

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Loss functions between PCA-DNN model and PCA-LSTM model. by Cihun-Siyong Alex Gong (11874066)

Loss function value changes in CNN training changes with epochs for both training dataset and testing dataset. by Jiaxi Wang (545353)

GD and soft loss function (Loss_S) parameters are optimized through the hyperparameter tuning process within their search spaces. by Burcu Ozek (16949357)