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

“…<p dir="ltr">This dataset was designed to fine-tune code-generation models for converting algorithmic statements written in Kannada or English into Python code. …”

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

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

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

“…Decoding from functional magnetic resonance imaging data revealed that solutions from the SF&GPI algorithm were activated on test tasks in visual and prefrontal cortex. …”

Algorithmic experimental parameter design. by Chuanxi Xing (20141665)

“…The results of numerical simulations and sea trial experimental data indicate that the use of subarrays comprising 5 and 3 array elements, respectively, is sufficient to effectively estimate 12 source angles. …”

Spatial spectrum estimation for three algorithms. by Chuanxi Xing (20141665)

“…The results of numerical simulations and sea trial experimental data indicate that the use of subarrays comprising 5 and 3 array elements, respectively, is sufficient to effectively estimate 12 source angles. …”

Pseudo-code for the study design model. by Jianpeng Zhang (528185)

Subjects:

The genome coding scheme. by Wenbing Shi (5806160)

Subjects:

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)

Source Code and Dataset by Swathi Ganesan (14394924)

GA pseudo-code. by Jianpeng Zhang (528185)

Subjects:

The speciation of ANEAT model evolution. by Wenbing Shi (5806160)

Subjects:

The fitness of ANEAT model evolution. by Wenbing Shi (5806160)

Subjects:

The fitness of NANEAT model evolution. by Wenbing Shi (5806160)

Subjects:

The speciation of NANEAT model evolution. by Wenbing Shi (5806160)

Subjects:

Temporal response patterns determined by the GMM clustering algorithm across varying primary stimulus parameters (amplitude or onset ramp velocity) of all test stimuli. by Dinh K. Tang (20469082)

The construction process of the CGO prediction model. by Wenbing Shi (5806160)

Subjects:

The structure of the NANEAT model corresponds to the optimal species genome. by Wenbing Shi (5806160)

Subjects:

The structure of the ANEAT model corresponds to the optimal species genome. by Wenbing Shi (5806160)

Subjects:

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

“…<p dir="ltr">The data in this repository accompanies the paper 'Efficient Event-based Delay Learning in Spiking Neural Networks'</p><p dir="ltr">The data relates to 4 benchmarks:</p><ol><li>Spiking Heidelberg Digits (SHD).…”