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

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. …”

Comparison of different optimization algorithms. by Hang Zhao (143592)

Subjects: “…crayfish optimization algorithm…”

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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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. …”

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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Flowchart of the study. by Usman Haider (12630481)

“…<div><p>This paper presents a digital beamforming technique with low radio frequency (RF) complexity that can preserve antenna weights between the antenna aperture and the digital baseband processing unit. Each antenna subarray connects a separate RF chain and it can only transmit one data stream. …”

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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