Multiclass comparison of algorithms on test data for KDDCup 99. by Arati Behera (19864844)

Relevant computed image data. by Zhaoyu Ku (20660546)

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Multiclass comparison of algorithms on test data for CIC-IoT23. by Arati Behera (19864844)

Comparison of optical and silicon-based neural network implementations. by Reyhane Ahmadi (14857363)

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Comparison of power consumption in optical and silicon-based neural network implementations. by Reyhane Ahmadi (14857363)

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The relevant data file for this article. by Linsha Liu (20378293)

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

Accuracy of different electrical and optical neural networks for various input noise levels. by Reyhane Ahmadi (14857363)

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Accuracy of different electrical and optical neural network on Caltech and ETH-80 data sets. by Reyhane Ahmadi (14857363)

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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).…”

The main components and data flow of the proposed algorithm. by Raed Alharthi (18340157)

Comparison of feature-based and Uniform Manifold Approximation and Projection (UMAP)-based spike sorting for neuron classification. by Daniel Suárez-Barrera (22676654)

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Comparison of Uniform Manifold Approximation and Projection (UMAP)-based and feature-based spike sorting on synthetic data. by Daniel Suárez-Barrera (22676654)

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

Summary of relevant works. by Bashir Olaniyi Sadiq (22478011)

The material characteristics of the components. by Shangyang Jin (21772466)

Beyond Global Metrics: A Zone-Stratified Diagnostic Framework Based on Confusion Matrix Components by Tareef Fadhil Raham (22407880)

“…<i>Beyond Global Metrics: A Zone-Stratified Diagnostic Framework Based on Confusion Matrix Components.</i> Manuscript (under editorial considerations).…”

Mapping between textual description and Algorithm 1 components. by Adel Alshamrani (22022154)

Communication Overhead by Component. by Mohsen H. Alhazmi (22756263)

“…We propose Adaptive Federated Clustering (AFC), a novel framework that addresses these challenges through three key innovations: (1) adaptive client selection based on computational capacity and data relevance, (2) hierarchical aggregation organizing clients into clusters for localized updates, and (3) sparsity- and quantization-based model compression. …”

Security Component Analysis. by Mohsen H. Alhazmi (22756263)

“…We propose Adaptive Federated Clustering (AFC), a novel framework that addresses these challenges through three key innovations: (1) adaptive client selection based on computational capacity and data relevance, (2) hierarchical aggregation organizing clients into clusters for localized updates, and (3) sparsity- and quantization-based model compression. …”