Comparison of edge detector and CHT in detecting droplets. by Manibarathi Vaithiyanathan (6655274)

Meta data for selected plots of "Optimal sampling of tensor networks targeting wave function’s fast decaying tails" by Marco Ballarin (17780767)

Schematic diagram of RRT-Connect algorithm expansion. by Zhenggang Wang (1753657)

Subjects: “…target gravitational function…”

Node matching step 1. by Shuwen Wang (457921)

Convergence of the Cut Value of QFMA as a function of steps for the G1 problem. by Máté Tibor Veszeli (12160786)

Comparison of experimental results in path steps for 8–12 irregular obstacles. by Ying Li (38224)

Overview of the algorithm used to calculate Lyapunov exponents for assessing the stability and chaotic behavior of dynamical systems. by Adil Jhangeer (9711917)

Schematic diagrams of M-shaped wave. by Dapeng Wang (250459)

Visualization of the RITSS algorithm. by Julian Hecker (758791)

Python scripts used to model CPU errors by Poisson distribution density mass function and to draw graph of Poisson events (needs Matplot, SciPy, PysimpleGUI and NumPy) by Santhosh Kumar Rajamani (13023678)

Figures and supplemental figures for "Optimal sampling of tensor networks targeting wave function’s fast decaying tails" by Marco Ballarin (17780767)

“…<p dir="ltr">Figures and supplemental figures for "Optimal sampling of tensor networks targeting wave function’s fast decaying tails". The supplemental figures are the data from the "Dibona" machine regarding the energy consumption of the algorithm. …”

Animations as supplemental material for "Optimal sampling of tensor networks targeting wave function’s fast decaying tails" by Marco Ballarin (17780767)

The real NGD values, one-step ahead training set predictions, and multi-step ahead test set predictions using the AI-AFTER algorithm for Kayseri. by Burak Alakent (463512)

Solving steps. by Mengkai Liu (13919242)

Comparison of algorithm search curves. by Bowen Li (200859)

“…Finally, through dynamic adaptive cuckoo search (DACS), the step size is automatically adjusted according to the convergence speed of the objective function of RBF, and the efficiency and accuracy of RBF in different search stages are balanced. …”

Verification of the in-line PS function. by Raul Castañeda (13932971)

Available functions in the utility package. by Raul Castañeda (13932971)

Instance count of all output steps based on schedulability. by Zhiqun Lin (1429501)

Subjects:

Mean waiting time trend with static and dynamic steps. by Ludovica Adacher (11238189)

EALM algorithm. by Weibo Wang (782424)