Similarity between the allegiance matrices of the multiplex SC-FC graph, the FC graph alone, and the SC graph alone, as a function of the topological scale for the group. by Arian Ashourvan (6685232)

Algorithm of the brightness scale calibration experiment. by Krzysztof Petelczyc (3954203)

“…<p>In the algorithm, the following variables were used: “I” denotes the current luminous intensity of the reference diode, “inc” denotes the current difference between reference and target diode luminous intensity; “cnt” is the current number of performed trials, while “correct” is a counter of correct answers in cnt trials, both of them are counted separately for every settings of I and inc. …”

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

Damping oscillation function (before adding random numbers). by Fujun Wang (96184)

Comparison between different PSO algorithms on function 4–6. by Lai Xu (1828831)

Comparison between different PSO algorithms on function 1–3. by Lai Xu (1828831)

Comparison between different PSO algorithms on function 7–8. by Lai Xu (1828831)

Image_2_Identification and verification of diagnostic biomarkers in recurrent pregnancy loss via machine learning algorithm and WGCNA.tif by Changqiang Wei (11454415)

“…This profile underwent differential expression analysis, WGCNA, functional enrichment, and subsequent analysis of RPL gene expression using LASSO regression, SVM-RFE, and RandomForest algorithms for hub gene screening. …”

Image_1_Identification and verification of diagnostic biomarkers in recurrent pregnancy loss via machine learning algorithm and WGCNA.tif by Changqiang Wei (11454415)

“…This profile underwent differential expression analysis, WGCNA, functional enrichment, and subsequent analysis of RPL gene expression using LASSO regression, SVM-RFE, and RandomForest algorithms for hub gene screening. …”

Image_3_Identification and verification of diagnostic biomarkers in recurrent pregnancy loss via machine learning algorithm and WGCNA.tif by Changqiang Wei (11454415)

“…This profile underwent differential expression analysis, WGCNA, functional enrichment, and subsequent analysis of RPL gene expression using LASSO regression, SVM-RFE, and RandomForest algorithms for hub gene screening. …”

The comparison of TL before and after optimization. by Shangyang Jin (21772466)

The comparison of TL before and after optimization. by Shangyang Jin (21772466)

Comparison of loss function curves before and after improvement. by Xiaozhou Feng (2918222)

RMSE values of different algorithms for different bands in the "Kherson" region. by YueSheng Jiang (19267984)

RMSE values of different algorithms for different bands in the "PY" region. by YueSheng Jiang (19267984)

Application of the algorithm to unseen data. Presynaptic neurons labelled by rabies viral injection into layer 2/3 primary visual cortex in Penk-Cre mice. by Adam L. Tyson (10892822)

The losses of the training process before and after the optimization of loss function. by Peihan Wen (6324315)

Path comparison before and after smoothing. by Zhenggang Wang (1753657)

Comparison before and after path pruning. by Zhenggang Wang (1753657)

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