Table_1_Clinical Functional Seizure Score (CFSS): a simple algorithm for clinicians to suspect functional seizures.DOCX by Mohammad Dashtkoohi (15417886)

Probably pathogenic variants (algorithms). by Felipe Fidalgo (642532)

Compare the test functions. by Yanqiu Li (683621)

a) FO Function, b) FI function. by Huang Jiexian (17060975)

“…The SRL32 primitive (Reconfigurable Look up Tables—RLUTs) and DPR (Dynamic Partial Reconfiguration) are employed to reconfigure single round MISTY1 / KASUMI algorithms on the run-time. The RLUT based architecture attains dynamic logic functionality without extra hardware resources by internally modifying the LUT contents. …”

<i>K</i>-CDFs: A Nonparametric Clustering Algorithm via Cumulative Distribution Function by Jicai Liu (11419050)

“…<p>We propose a novel partitioning clustering procedure based on the cumulative distribution function (CDF), called <i>K</i>-CDFs. …”

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

Detailed information of benchmark functions. by Guangwei Liu (181992)

“…In Case 1, the GJO-GWO algorithm addressed eight complex benchmark functions. …”

Predictions from a Universal Value Function Approximator (UVFA) algorithm. by Sam Hall-McMaster (10343795)

The empirical distribution function and fitted distribution functions for data sets <i>Q</i> and <i>T</i>. by Salem A. Alyami (10572611)

The signal detection algorithm for constructing a neurometric function (the probability of segregation as a function of time) generates acceptable buildup fits at <i>DF</i> = 1, 3, 6, 9. by Quynh-Anh Nguyen (847240)

“…Parameters <i>N</i>_<i>in</i> and <i>C</i>_<i>th</i> are chosen to yield SEM similar to those observed in the spike count data [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1008152#pcbi.1008152.ref001" target="_blank">1</a>, (Fig.3A in Ref)] and to yield the least-squares error of the experimental buildups (dashed, extracted from [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1008152#pcbi.1008152.ref001" target="_blank">1</a>, (Fig.4 in Ref)] and the computer-simulated neurometric functions (solid) for <i>DF</i> = 1, 3, 6, 9. …”

Search Algorithms and Loss Functions for Bayesian Clustering by David B. Dahl (11761055)

“…<p>We propose a randomized greedy search algorithm to find a point estimate for a random partition based on a loss function and posterior Monte Carlo samples. …”

Face matching performance as a function of test condition for Study 1 (threshold = 0.5). by Daniela Barragan (13146762)

Represention of the anneal schedules used as a function of the dimensionless anneal parameter <i>s</i>. by John Golden (9946327)

Loss function variation curve. by Chunhua Yang (346871)

Subjects:

Standard benchmark functions used for the experimentation of EOSA and other similar optimization algorithms. by Tehnan I. A. Mohamed (16846175)

A two-particle GPSA solving a one-dimensional UMO function. by Yoshikazu Yamanaka (10325863)

“trend+var” algorithm. by Roman Olson (6577004)

Matlab code of a function used in S2 File. by Hiroko Kato Solvang (5718250)

Algorithmic assessment reveals functional implications of GABRD gene variants linked to idiopathic generalized epilepsy by Ayla Arslan (17943365)

“…</p> <p>The study employs a combination of in silico algorithms to analyze 82 variants of unknown clinical significance of GABRD gene sourced from the ClinVar database. …”

Performance of algorithms compared to a smaller <i>RNN.</i> by Swathi Anil (17382903)