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

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

“…The goal of this paper is to examine several extensions to KGR/GPoG, with the aim of generalising them a wider variety of data scenarios. The first extension we consider is the case of graph signals that have only been partially recorded, meaning a subset of their elements is missing at observation time. …”

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. …”

CY45-0.5/1#9 Code file for data processing and prediction results. by Yanhua Xian (21417128)

Impact of multiunit merging on neural information encoding. by Daniel Suárez-Barrera (22676654)

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The CGO risk prediction process based on data augmentation and neuroevolution. by Wenbing Shi (5806160)

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

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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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Algorithm process. by Wei Cui (92129)

GA pseudo-code. by Jianpeng Zhang (528185)

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The Search process of the genetic algorithm. by Wenguang Li (6528113)

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

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The construction process of the FCM clustering algorithm. by Xini Fang (20861990)

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Processed results from ECG data with the P-T algorithm. by Daehyun Kwon (11985629)

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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Comparative analysis of spike sorting using Uniform Manifold Approximation and Projection (UMAP) vs. feature-based methods in in vivo extracellular recordings. by Daniel Suárez-Barrera (22676654)

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Spatiotemporal spike sorting on multi-electrode array (MEA) data: Uniform Manifold Approximation and Projection (UMAP) vs. SpyKING CIRCUS (SC). by Daniel Suárez-Barrera (22676654)

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Uniform Manifold Approximation and Projection (UMAP)-based sorting enhances detection of low-firing rate neurons and boosts mutual information. by Daniel Suárez-Barrera (22676654)

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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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Multi-sensor fusion process and algorithm workflow. by Hongliang Zou (20707270)