Fig 7 - by Xiaogang Li (299205)

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The normalized acoustic resistance (blue lines) and reactance (red dotted lines) of the optimization case in Fig 7. by Xiaogang Li (299205)

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Cross section of the metagrating and the distribution of effective homogeneous layers. by Xiaogang Li (299205)

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Example change statistic implementations. by Alex Stivala (8356257)

“…We use a simulation study to assess the accuracy of the EE algorithm for ALAAM parameter estimation and statistical inference, and demonstrate the use of ALAAMEE with empirical examples using both small (fewer than 100 nodes) and large (more than 10 000 nodes) networks.…”

Implementing the branch-and-cut approach for a general purpose Benders’ decomposition framework - Computational results by S Maher (9883616)

“…A branch-and-cut approach for Benders’ decomposition has been implemented within the constraint integer programming solver SCIP using a plugin-based design to allow for a wide variety of extensions and customisations to the algorithm. …”

<b>Codes for "Fatigue analysis of wind turbine and load reduction through wind-farm-level yaw control"</b> by Yize Wang (19535173)

“…<p dir="ltr">The farm-level yaw control optimization algorithm Codes for "Fatigue analysis of wind turbine and load reduction through wind-farm-level yaw control"</p>…”

Accuracy of different electrical and optical neural networks for various input noise levels. by Reyhane Ahmadi (14857363)

Ms.FPOP: A Fast Exact Segmentation Algorithm with a Multiscale Penalty by Arnaud Liehrmann (10970682)

“…<p>Given a time series in <math><mrow><mrow><mi>R</mi></mrow><mi>n</mi></mrow></math> with a piecewise constant mean and independent noises, we propose an exact dynamic programming algorithm for minimizing a least-squares criterion with a multiscale penalty, favoring well-spread changepoints. …”

Elements: Multiparticle collision dynamics simulations of mesoscale hydrodynamic interactions in complex soft materials and environments by Michael Howard (19421473)

Comparison of performance between our next reaction implementation and the Python library from Ref. [3]. by Samuel Cure (22250922)

Data Sheet 1_Fast forward modeling and response analysis of extra-deep azimuthal resistivity measurements in complex model.docx by Pan Zhang (206408)

“…Considering the increased detection range of EDARM and the requirements for computational efficiency, this paper presents a 2.5-dimensional (2.5D) finite element method (FEM). By leveraging the symmetry of simulated signals in the spectral domain, the algorithm reduces computation time by 50%, significantly enhancing computational efficiency while preserving accuracy. …”

Algorithms example of segmentation task through ZdensityRODE and AMPDE. by Gabriel Galeote-Checa (20613878)

Efficient Algorithms for GPU Accelerated Evaluation of the DFT Exchange-Correlation Functional by Ryan Stocks (16867476)

“…In this work, we present a comparative study of four GPU-accelerated algorithms for evaluating the KS-DFT exchange–correlation (XC) potential with an atom-centered Gaussian basis. …”

Code by Baoqiang Chen (21099509)

“…We divided the dataset into training and test sets, using 70% of the genes for training and 30% for testing. We implemented machine learning algorithms using the following R packages: rpart for Decision Trees, gbm for Gradient Boosting Machines (GBM), ranger for Random Forests, the glm function for Generalized Linear Models (GLM), and xgboost for Extreme Gradient Boosting (XGB). …”

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

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

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

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

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