BP schematic diagram. by Ruiyu Zhan (21602031)

“…We performed comparative analyses against other methodologies across various functions and public datasets to assess their effectiveness. …”

DNAmethylationfeature importance ranking. by Ruiyu Zhan (21602031)

“…We performed comparative analyses against other methodologies across various functions and public datasets to assess their effectiveness. …”

Pearson correlation heatmap of DNAmethylation. by Ruiyu Zhan (21602031)

“…We performed comparative analyses against other methodologies across various functions and public datasets to assess their effectiveness. …”

Comparison of experimental and simulated data across frequency differences and tactile Conditions, with audio and tactile input spread profiles. by Farzaneh Darki (22076051)

Fig 6 - by Caroline C. McGrouther (5216153)

Right Knee fNIRS MI Dataset by Hammad Gilani (8060012)

“…<p><br></p><p dir="ltr">This dataset contains functional near-infrared spectroscopy (fNIRS) signals recorded during motor imagery (MI) tasks of lower limb movements. …”

Left Knee fNIRS MI Dataset by Hammad Gilani (8060012)

“…<p><br></p><p dir="ltr">This dataset contains functional near-infrared spectroscopy (fNIRS) signals recorded during motor imagery (MI) tasks of lower limb movements. …”

Left Ankle fNIRS MI Dataset by Hammad Gilani (8060012)

“…<p><br></p><p dir="ltr">This dataset contains functional near-infrared spectroscopy (fNIRS) signals recorded during motor imagery (MI) tasks of lower limb movements. …”

Bias of frequencies estimates—the balanced case: by Henri Christian Junior Tsoungui Obama (10432244)

Bias of frequencies estimates – the unbalanced case: by Henri Christian Junior Tsoungui Obama (10432244)

Network pharmacology analysis. by Jinghui Xie (3942290)

Dataset: EEG-Controlled Exoskeleton for Walking and Standing - A Longitudinal Study of Healthy Individuals by Shantanu Sarkar (20848745)

Two datasets. by Salem A. Alyami (10572611)

“…<div><p>This article examines the estimate of <i>ϑ</i> = <i>P</i> [<i>T</i> < <i>Q</i>], using both Bayesian and non-Bayesian methods, utilizing progressively first-failure censored data. …”

Histogram of MCMC estimates of <i>ϑ</i>. by Salem A. Alyami (10572611)

“…<div><p>This article examines the estimate of <i>ϑ</i> = <i>P</i> [<i>T</i> < <i>Q</i>], using both Bayesian and non-Bayesian methods, utilizing progressively first-failure censored data. …”

Trace plot of MCMC estimates of <i>ϑ</i>. by Salem A. Alyami (10572611)

“…<div><p>This article examines the estimate of <i>ϑ</i> = <i>P</i> [<i>T</i> < <i>Q</i>], using both Bayesian and non-Bayesian methods, utilizing progressively first-failure censored data. …”

The POFIF-C samples from the real data sets. by Salem A. Alyami (10572611)

“…<div><p>This article examines the estimate of <i>ϑ</i> = <i>P</i> [<i>T</i> < <i>Q</i>], using both Bayesian and non-Bayesian methods, utilizing progressively first-failure censored data. …”

Enrichment analysis and PPI network analysis for key modules. by Bei Tian (1319283)

General Chemically Intuitive Atom- and Bond-Level DFT Descriptors for Machine Learning Approaches to Reaction Condition Prediction by Miguel Nouman (21557202)

“…Remarkably, the best performing neural network trained on hybrid embeddings outperforms the best purely structural model investigated despite the latter benefiting from of an embedding strategy with 267 times more data points than the one used for generating and embedding hybrid descriptors, with both strategies being unsupervised learning algorithms that share considerable conceptual and architectural similarities.…”

General Chemically Intuitive Atom- and Bond-Level DFT Descriptors for Machine Learning Approaches to Reaction Condition Prediction by Miguel Nouman (21557202)

“…Remarkably, the best performing neural network trained on hybrid embeddings outperforms the best purely structural model investigated despite the latter benefiting from of an embedding strategy with 267 times more data points than the one used for generating and embedding hybrid descriptors, with both strategies being unsupervised learning algorithms that share considerable conceptual and architectural similarities.…”

General Chemically Intuitive Atom- and Bond-Level DFT Descriptors for Machine Learning Approaches to Reaction Condition Prediction by Miguel Nouman (21557202)

“…Remarkably, the best performing neural network trained on hybrid embeddings outperforms the best purely structural model investigated despite the latter benefiting from of an embedding strategy with 267 times more data points than the one used for generating and embedding hybrid descriptors, with both strategies being unsupervised learning algorithms that share considerable conceptual and architectural similarities.…”