The topology of the NYN. by Yi Tao (178829)

Subjects: “…evolutionary genetic algorithm…”

The result of Wilcoxon signed-rand test. by Yi Tao (178829)

Subjects: “…evolutionary genetic algorithm…”

The Simulation and optimization process of pipe diameter selection. by Yi Tao (178829)

Subjects: “…evolutionary genetic algorithm…”

Optional pipe diameter and unit price of NYN. by Yi Tao (178829)

Subjects: “…evolutionary genetic algorithm…”

Optional pipe diameter and unit price of HN. by Yi Tao (178829)

Subjects: “…evolutionary genetic algorithm…”

The topology of HN. by Yi Tao (178829)

Subjects: “…evolutionary genetic algorithm…”

Information of nodes and pipes of HN. by Yi Tao (178829)

Subjects: “…evolutionary genetic algorithm…”

Network structure of perception fusion algorithm. by Weilin Wu (13736)

Subjects:

The eVIP algorithm uses RNA-seq data to predict the function of somatic mutations. by Alexis M. Thornton (11068403)

“…<p>(A) Overview of the experimental approach (B) Schematic of the eVIP decision tree-based eVIP algorithm. The impact test is a Kruskal-Wallis test of the three distributions: wild-type replicate self-correlation, mutant replicate self-correlation, and wild-type versus mutant correlation. …”

Performance of adversarial training on three public datasets. by Bing Zhang (129)

Subjects:

Performance of the attention filter on three public datasets. by Bing Zhang (129)

Subjects:

The results of each test function. by Yuhang Wang (332111)

Recombinant mapping narrows region of interest to identify a loss-of-function allele of <i>mttp.</i> by McKenna Feltes (11242085)

Subjects:

Comparison of CFMM performance with and without Fusion Loss, with and without Cross-Attention, and with different parameters. by Chong Zhang (418677)

Subjects:

Performance of double comparison learning on three public datasets. by Bing Zhang (129)

Subjects:

Comparison of deconvolution and optimization algorithms on a batch of data. by Ali-Kemal Aydin (10968731)

“…Both experimental data have been resampled at 50ms and used to compute a set of TFs (in orange) either with direct deconvolution approaches (Fourier or Toeplitz methods, middle-upper panel TFs) or with 1-Γ function optimization performed by 3 different algorithms (middle-lower panel TFs). …”

AP values of different methods on the three datasets, including four indicators: AP@50, AP@75, AP@M, and AP@L. by Xunqian Xu (21261899)

Subjects:

Key gene identification based on two machine learning algorithms. by Lijun Guo (605276)

FPS values of different methods on the three datasets, where red represents the COCO dataset, yellow represents the MPII dataset, and green represents the HP dataset. by Xunqian Xu (21261899)

Subjects:

Ap values of different methods on the three datasets. AP values include four indicators: AP@50, AP@75, AP@M, and AP@L. by Xunqian Xu (21261899)

Subjects: