Numbers of iterations (#Ite) and eigenvalue calculations (#Eig) in the DC algorithm on the random and chain graph datasets. حسب Tomokaze Shiratori (9635271)

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Main code. حسب Jingguo Bi (21439766)

Computation time as a function of the sample size on the chain graph dataset. حسب Tomokaze Shiratori (9635271)

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Log-likelihood as a function of the number of selected edges on the chain graph dataset (black dashed line: The true number of edges). حسب Tomokaze Shiratori (9635271)

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Computation time as a function of the sample size on the random graph dataset. حسب Tomokaze Shiratori (9635271)

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F1 score of edges selected through cross-validation on the chain graph dataset. حسب Tomokaze Shiratori (9635271)

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Log-likelihood as a function of the number of selected edges on the random graph dataset (black dashed line: The true number of edges). حسب Tomokaze Shiratori (9635271)

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Examples of ground-truth graph structures with (<i>p</i>, <i>n</i>_≠0) = (10, 10). حسب Tomokaze Shiratori (9635271)

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Number of edges selected through cross-validation on the chain graph dataset. حسب Tomokaze Shiratori (9635271)

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Number of edges selected through cross-validation on the random graph dataset. حسب Tomokaze Shiratori (9635271)

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Graphs of the regularization terms. حسب Tomokaze Shiratori (9635271)

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F1 score of a given number of selected edges on the chain graph dataset. حسب Tomokaze Shiratori (9635271)

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Computation time as a function of the number of variables on the chain graph dataset. حسب Tomokaze Shiratori (9635271)

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Computation time as a function of the number of variables on the random graph dataset. حسب Tomokaze Shiratori (9635271)

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F1 score of a given number of selected edges on the random graph dataset. حسب Tomokaze Shiratori (9635271)

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F1 score of edges selected through cross-validation on the random graph dataset. حسب Tomokaze Shiratori (9635271)

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Pseudo-code of large neighborhood search (<i>LNS</i>) algorithm. حسب Jiren CAO (20442214)

TIR-Learner v3: New generation TE annotation program for identifying TIRs حسب Tianyu Lu (18856792)

"…<h3><b>Abstract</b></h3><p dir="ltr">TIR-Learner is an ensemble pipeline for Terminal Inverted Repeat (TIR) transposable elements annotation, which combines homology-based detection, de novo tools and convolutional neural network to classify candidate sequences into five major TIR superfamilies. …"

Chromosome coding. حسب Junjie He (700642)

Open-source code for the Spatial Optimization Model for Land Use (SSFLA-MLAS) حسب bowen pang (21837359)

"…<p dir="ltr">The open-source content is the source code of a land use spatial optimization model (SSFLA-MLAS) that couples the spatial leapfrog algorithm with multi-level multi-agent systems. …"