ML algorithms in cyber security. by Abdullah Asım Yılmaz (20715311)

Data and code resources. by Sam Hall-McMaster (10343795)

“…This activation had a functional connection to behavior in that stronger activation of SF&GPI solutions in visual areas was associated with increased behavioral reuse. These findings point to a possible neural implementation of an adaptive algorithm for generalization across tasks.…”

The run time for each algorithm in seconds. by Edward Antonian (21453161)

“…We find evidence that the generalised GLS-KGR algorithm is well-suited to such time-series applications, outperforming several standard techniques on this dataset.…”

K-shortest path algorithm, finding count, and OD algorithm. by Jin Ki Eom (21192426)

The folder containing the code is provided as supportive documentation associated with this paper. by Quxi Kuang (22493270)

Subjects:

Dataset for Fine-Tuning Code Generation Models: Kannada-English Algorithmic Statements and Python Code by Goutami Sooda (20714729)

The comparison of results from the proposed architecture and state-of-the-art algorithms on the UNSW-B15, NSL-KDD and KDDCUP’99 dataset. by Abdullah Asım Yılmaz (20715311)

Folder with all data and algorithms by Jorge Servert Lerdo de Tejada (22290001)

A* Path-Finding Algorithm to Determine Cell Connections by Max Weng (22327159)

Code used for data analysis in this study. by Nourin Sultana (22339463)

Subjects:

a. How various statistical models account for modulation classification performance across the entire dataset. by Chris Scholes (3309477)

Algorithm testing. by Ziad M. Ali (12516532)

Subjects:

XGBoost odor prediction model: finding the structure-odor relationship of odorant molecules using the extreme gradient boosting algorithm by Pankaj Tyagi (20147683)

UAV target finding and target tracking. by Yuanhong Dan (20570631)

UAV target finding and target tracking. by Yuanhong Dan (20570631)

The parameter setting of the evolutionary neural network. by Wenbing Shi (5806160)

Subjects:

The genome coding scheme. by Wenbing Shi (5806160)

Subjects:

Model comparison between our model-free algorithm (here MF*) and SARSA. by Carlos A. Velázquez-Vargas (19751567)

Research data for paper: Efficient Event-based Delay Learning in Spiking Neural Networks by Balázs Mészáros (16890225)

“…Our method supports multiple spikes per neuron and introduces a delay learning algorithm that can, in contrast to previous methods, also be applied to recurrent Spiking Neural Networks. …”

Bagging Model Algorithm Flow. by Wen Yu (384130)