Performance of algorithms outside the training species. by Sven B. Gould (12237287)

“…Each Venn diagram of the top panel shows an overlap between predicted (left circles, colour-coded based on the algorithms used) and experimentally verified organelle proteomes (right circles, grey). …”

A framework for improving localisation prediction algorithms. by Sven B. Gould (12237287)

“…The training data should ideally be collected from a range of diverse species and for each be based on different experimental techniques that support a training protein’s localisation (e.g. reporters, mass spectrometry, coexpression, interactions). …”

Computational Procedure of the Particle Swarm Optimization (PSO) algorithm. by Meijun Shang (22806461)

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

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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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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Experimental steps of modulation pattern recognition method based on IABLN algorithm. by Ting Xie (191025)

“…<p>Experimental steps of modulation pattern recognition method based on IABLN algorithm.…”

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

Main Experimental Parameters of Baseline Algorithms. by Ming Gao (115719)

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Experimental data of ZFD-Net algorithm for defects. by Yang Gao (18005)

Statistical test of experimental results of NAFPSO and PSO algorithm. by Huichao Guo (14515171)

Comparison of experimental data from three different algorithms. by Xiaobing Chen (572034)

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The source code of LazyAct. by Hongjie Zhang (136127)

“…However, the high computational cost of policies based on deep neural networks restricts their practical application. …”

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

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The genome coding scheme. by Wenbing Shi (5806160)

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Experimental results of NAFPSO algorithm with pipeline complexity of 0.7. by Huichao Guo (14515171)

Experimental results of NAFPSO algorithm with pipeline complexity of 0.5. by Huichao Guo (14515171)

Experimental results of NAFPSO algorithm with pipeline complexity of 0.6. by Huichao Guo (14515171)