Total primary energy demand by fuel in China. حسب Da Lian (18880882)

Reproducing kernel-based semiparametric functional smoothed score estimation with binary responses حسب Meichen Liu (8168148)

<i>hi</i>PRS algorithm process flow. حسب Michela C. Massi (14599915)

"…<b>(C)</b> The whole training data is then scanned, searching for these sequences and deriving a re-encoded dataset where interaction terms are binary features (i.e., 1 if sequence <i>i</i> is observed in <i>j</i>-th patient genotype, 0 otherwise). …"

Schematic representation of semi-automated algorithm for organoids analyzing. حسب Anna Demchenko (18449439)

Proposed model tuned hyperparameters. حسب Subathra Gunasekaran (19492680)

"…To select the most informative features for effective segmentation, we utilize an advanced meta-heuristics algorithm called Advanced Whale Optimization (AWO). …"

The workflow of the proposed model. حسب Subathra Gunasekaran (19492680)

"…To select the most informative features for effective segmentation, we utilize an advanced meta-heuristics algorithm called Advanced Whale Optimization (AWO). …"

ResNeXt101 training and results. حسب Subathra Gunasekaran (19492680)

"…To select the most informative features for effective segmentation, we utilize an advanced meta-heuristics algorithm called Advanced Whale Optimization (AWO). …"

Proposed model specificity and DSC outcomes. حسب Subathra Gunasekaran (19492680)

"…To select the most informative features for effective segmentation, we utilize an advanced meta-heuristics algorithm called Advanced Whale Optimization (AWO). …"

Accuracy comparison of proposed and other models. حسب Subathra Gunasekaran (19492680)

"…To select the most informative features for effective segmentation, we utilize an advanced meta-heuristics algorithm called Advanced Whale Optimization (AWO). …"

Architecture of ConvNet. حسب Subathra Gunasekaran (19492680)

"…To select the most informative features for effective segmentation, we utilize an advanced meta-heuristics algorithm called Advanced Whale Optimization (AWO). …"

Comparison of state-of-the-art method. حسب Subathra Gunasekaran (19492680)

"…To select the most informative features for effective segmentation, we utilize an advanced meta-heuristics algorithm called Advanced Whale Optimization (AWO). …"

Proposed model sensitivity outcome. حسب Subathra Gunasekaran (19492680)

"…To select the most informative features for effective segmentation, we utilize an advanced meta-heuristics algorithm called Advanced Whale Optimization (AWO). …"

Proposed ResNeXt101 operational flow. حسب Subathra Gunasekaran (19492680)

"…To select the most informative features for effective segmentation, we utilize an advanced meta-heuristics algorithm called Advanced Whale Optimization (AWO). …"

Supplementary Material for: Penalized Logistic Regression Analysis for Genetic Association Studies of Binary Phenotypes حسب Yu Y. (3096192)

"…Our estimate of m is the maximizer of a marginal likelihood obtained by integrating the latent log-ORs out of the joint distribution of the parameters and observed data. We consider two approximate approaches to maximizing the marginal likelihood: (i) a Monte Carlo EM algorithm (MCEM) and (ii) a Laplace approximation (LA) to each integral, followed by derivative-free optimization of the approximation. …"

Latent state estimations for experimental data with no stressors. حسب Samiul Alam (18563323)

Latent state estimations for experimental data with interruptions. حسب Samiul Alam (18563323)

Latent state estimations for experimental data with time limit. حسب Samiul Alam (18563323)

Latent state estimations for experimental data with interruptions for subject 18. حسب Samiul Alam (18563323)

Latent state estimations for experimental data with no stressors for subject 22. حسب Samiul Alam (18563323)

Latent state estimations for experimental data with no stressors for subject 17. حسب Samiul Alam (18563323)