The benchmark functions. by Shuhui Yu (1535500)

Average function evaluation times of the three optimization algorithms. by Shuhui Yu (1535500)

Variations of loss functions versus epoch number. by Xueliang Guo (4797057)

Hist-8000 sequence similarity scores are closer to the ground truth than the corresponding Sum-of-learnt-Trigrams scores. (NW, Hist-8000) and (NW, Hist-SDM12) are both higher than... by Frixos Papadopoulos (22001664)

Accelerated MPC Algorithms and Augmented System Design for Legged Robots by John Ndegwa Nganga (21088838)

“…The approach is powered by a newly introduced algorithm, named the modified Recursive Newton Euler Algorithm~(mRNEA), which is inspired by classical RNEA, and computes the dynamics information pre-multiplied with a fixed vector. …”

Summary of the contrasts obtained from the normalized images for both inclusions as a function of the host type and the wavelength. by María Victoria Waks-Serra (21578611)

The image of the Aekley function. by Zhengyu Xu (8550660)

HIV exposure risk algorithm. HIV exposure risk algorithm based on available data from the Tonse Padmozi trial. by Anna M. Leone (22486372)

Evolution of the rescaled hydraulic diameter () and complexity () in both simulations and seal tomograms as a function of simulation timestep and relative age (). by Jonathan E Kings (20818367)

Explained variance ration of the PCA algorithm. by Abeer Aljohani (18497914)

Subjects:

The ALO algorithm optimization flowchart. by Wenjing Wang (181404)

“…The average running time of the proposed algorithm in Sphere function and Griebank function was 2.67s and 1.64s, respectively. …”

The IALO algorithm solution flowchart. by Wenjing Wang (181404)

“…The average running time of the proposed algorithm in Sphere function and Griebank function was 2.67s and 1.64s, respectively. …”

Data pre-processing and identification of DEGs. by Ziyang Liu (242055)

The impact of extrinsic noise sources on the measured SNR is plotted for both CW and TG against varying optical filter magnitudes. by Nicholas H. Vitale (20469289)

Functional Projection <i>K</i>-means by Roberto Rocci (16022201)

“…In contrast to existing literature, which largely considers the smoothing as a pre-processing step, in our proposal regularization is integrated with the identification of both subspace and cluster partition. …”

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

“…Kohn–Sham density functional theory (KS-DFT) has become a cornerstone for studying the electronic structure of molecules and materials. …”

Comprehensive Re, F1 and Pre values of FcaNet-CycleGAN model. by Xiaojun Wang (50332)

Spike sorting performance dependence on pre-recording duration. by Tjitse van der Molen (20391106)

The pseudocode for the NAFPSO algorithm. by Huichao Guo (14515171)

“…The experimental results show that compared with the traditional particle swarm optimization algorithm, NACFPSO performs well in both convergence speed and scheduling time, with an average convergence speed of 81.17 iterations and an average scheduling time of 200.00 minutes; while the average convergence speed of the particle swarm optimization algorithm is 82.17 iterations and an average scheduling time of 207.49 minutes. …”

PSO algorithm flowchart. by Huichao Guo (14515171)

“…The experimental results show that compared with the traditional particle swarm optimization algorithm, NACFPSO performs well in both convergence speed and scheduling time, with an average convergence speed of 81.17 iterations and an average scheduling time of 200.00 minutes; while the average convergence speed of the particle swarm optimization algorithm is 82.17 iterations and an average scheduling time of 207.49 minutes. …”