A framework for improving localisation prediction algorithms. by Sven B. Gould (12237287)

Single-cell RNA sequencing analysis reveals the expression patterns of the prognostic signature across cellular subpopulations. by Xiangxin Wu (22320058)

If datasets are small and/or noisy, linear-regression-based algorithms for identifying functional groups outperform more complex versions. by Yuanchen Zhao (12905580)

“…Both versions are evaluated on the same synthetic datasets with a 3-group ground truth. Each algorithm return a set of coarsened <i>variables</i> (a grouping of species into three groups) and a <i>model</i> that uses these variables to predict the function. …”

Boxplots showcasing variability of additional key topological metrics obtained after 50 algorithm runs for the generation of a) chorionic vessels and b) villous vessels. by Diana C. de Oliveira (9220729)

Functions in nhppp. by Thomas A. Trikalinos (5785877)

“…We developed it to facilitate the sampling of event times in discrete event and statistical simulations. The package’s functions are based on three algorithms that provably sample from a target NHPPP: the time-transformation of a homogeneous Poisson process (of intensity one) via the inverse of the integrated intensity function; the generation of a Poisson number of order statistics from a fixed density function; and the thinning of a majorizing NHPPP via an acceptance-rejection scheme. …”

Structural diagram of the overall SCF-YOLO algorithm. by Yazhou Li (277980)

RTC-F solar cell: (a) <i>I</i>-<i>U</i> and (b) <i>P</i>-<i>U</i> characteristics. by Ziad M. Ali (12516532)

PWP201 solar module: (a) <i>I</i>-<i>U</i> and (b) <i>P</i>-<i>U</i> characteristics. by Ziad M. Ali (12516532)

Risk and density functions for standard relapse from remission condition to disease <i>b</i> condition (similar shapes for standard relapse to disease <i>a</i>). by Benoîte de Saporta (20454662)

PyNoetic’s classification module supports a range of popular and widely used ML classification models with just a single line of function call. by Gursimran Singh (575288)

Subjects:

MAE versus the number of iterations for different Gaussian noise levels: (a) <i>σ</i> = 10⁻² and (b) <i>σ</i> = 10⁻³. by Limin Ma (556873)

The result for the risk assessment on A, B, C bank using different features. by Jiaqing Huang (5018492)

Line chart plotted using the k-value selection algorithm: (A) system 1; (B) system 2; (C) system 3. by Jingnan Yan (20727331)

<b>Functional excitation-inhibition ratio indicates near-critical oscillations across frequencies</b> by Marina Diachenko (19739092)

“…<p dir="ltr">The <i>zip</i> file contains the code and data for the analyses/figures described in the paper titled "<b>Functional excitation-inhibition ratio indicates near-critical oscillations across frequencies</b>" published in September in 2024 in Imaging Neuroscience.…”

The results of LASSO regression algorithm. by Xue Fu (549661)

Comparison of Stage II-B and Stage II-A. by Ferhat Yuna (21519851)

Feto-placental vasculatures with non-central (A) and centralised (B) umbilical artery insertion. by Diana C. de Oliveira (9220729)

Adding a new function module. by Yukako Yamane (9034133)

(a) Random initialized population distribution (b) Good point set initialized population distribution. by Tengfei Ma (597633)

Fitness comparison on test function. by Kejia Liu (5699651)

“…The escape rate from local optima within DGEP reached 35% higher than what standard GEP could achieve. …”